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  <div>You’ll begin by setting up your Java development environment and exploring the fundamentals of AI. Further, you’ll build hands-on experience using tools and techniques such as Deeplearning4j and Spring AI in practical projects that employ powerful Java AI libraries. You’ll also learn to integrate your AI skills with Spring, leveraging its robust architecture to build smart applications.  </div><div> </div><div>Designed for developers with a basic understanding of Java and Spring, this course is suitable for anyone looking to enter the AI space without switching ecosystems or learning a new language. </div><div> </div><div>Ready to build the highly sought-after GenAI skills employers are actively seeking in just 3 weeks? Enroll now! </div><div><strong><br />Course Outline<br /></strong>This course consists of three modules.<br /><br /></div><div><strong>Course Syllabus</strong> <br /><br /></div><div><strong>Module 0: Welcome</strong></div><ul><li>Video: Course Introduction </li><li>Reading: General Information </li><li>Reading: Learning Objectives and Syllabus </li><li>Reading: Grading Scheme </li><li>Reading: How to Make the Most of This Course </li></ul><div> </div><div><strong>Module 1: AI Fundamentals with Java </strong></div><ul><li>Reading: Module Introduction and Learning Objectives </li><li>Video: Understanding AI Concepts in Java  </li><li>Video: Setting Up Your Java Environment for AI Development  </li><li>Lab: Environment Setup for AI Development in Java  </li><li>Video: Developing AI Algorithm in Java </li><li>Lab: Basic Prediction Model </li><li>Reading: Java Libraries for AI  </li><li>Video: Natural Language Processing with Java  </li><li>Lab: Sentiment Analysis for Product Reviews </li><li>Video: Image Recognition Basics in Java  </li><li>Reading: Popular Libraries for Image Recognition  </li><li>Lab: Product Image Recognition </li><li>Reading: Working with Deeplearning4j  </li><li>Module 1 Practice Quiz: AI Fundamentals with Java </li><li>Reading: Module 1 Summary: AI Fundamentals with Java </li><li>Reading: Glossary: AI Fundamentals with Java </li><li>Reading: Cheat Sheet: AI Fundamentals with Java </li><li>Module 1 Graded Quiz: AI Fundamentals with Java </li></ul><div> </div><div><strong>Module 2: Spring AI Integration </strong></div><ul><li>Reading: Module Introduction and Learning Objectives </li><li>Video: Introduction to Spring AI Framework  </li><li>Reading: Spring AI Architecture and Components  </li><li>Video: Setting Up Your First Spring AI Project  </li><li>Lab: Spring AI Service Layer: Customer Support Chatbot </li><li>Video: AI Service Layer with Spring  </li><li>Video: Implementing AI APIs with Spring Part 1 </li><li>Video: Implementing AI APIs with Spring Part 2 </li><li>Lab: Building a Recommendation System with Spring AI  </li><li>Video: Testing and Debugging Spring AI Applications  </li><li>Lab: Support Response Template AI Text Generator </li><li>Module 2: Practice Quiz: Spring AI Integration </li><li>Reading: Module 2 Summary: Spring AI Integration </li><li>Reading: Glossary: Spring AI Integration </li><li>Reading: Cheat Sheet: Spring AI Integration </li><li>Module 2 Graded Quiz: Spring AI Integration </li></ul><div> </div><div><strong>Module 3: Final Project and Assessment </strong></div><ul><li>Reading: Final Project Overview  </li><li>Lab: Final Project: Part A: Java AI Implementation </li><li>Lab: Final Project: Part B: Spring AI Framework Implementation </li><li>Final Project Submission </li><li>Final Exam </li></ul><div> </div><div><strong>Module 4: Course Wrap-up </strong></div><ul><li>Reading: Module Introduction and Learning Objectives </li><li>Video: Course Wrap-Up  </li><li>Reading: Congratulations and Next Steps </li><li>Reading: Team and Acknowledgments </li><li>Reading: Copyrights and Trademarks </li></ul><div> </div><div><strong>Course Rating and Feedback </strong></div><ul><li>Reading: Course Rating and Feedback </li></ul><div><br /></div><div><strong>Recommended Background</strong> </div><div>This course is designed for developers with a foundational understanding of Java and Spring. You should be familiar with core Java concepts such as variables, control flow, and object-oriented programming. A basic understanding of AI concepts is also recommended. </div>
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Generative AI for Java and Spring Development

This hands-on, project-driven course gives you the skills to bring artificial intelligence (AI) to life using Java and the Spring Framework. In just 3 weeks, you’ll learn how to build intelligent apps that create text, images, or recommendations quickly and become the go-to developer employers are looking for.To start, you’ll set up your Java development environment and dive into the core principles of AI. You’ll then move straight to building hands-on experience using tools and techniques such as Deeplearning4j and Spring AI in practical projects.

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  <div>Build the sought-after generative AI (GenAI) skills employers are looking for that will help to advance your career in customer and IT support.   <br /><br /></div><div><strong><em>You Will learn:</em></strong>  <br /><br /></div><ul><li>Job-ready skills to leverage GenAI to improve your customer interactions and streamline customer support operations using tools such as ChatGPT and Claude.ai </li><li>How to leverage GenAI to automate responses, create FAQs and user guides, and enable multilingual support  </li><li>How to leverage GenAI for SOP documentation, sentiment analysis, and proactive customer support  </li><li>A good understanding of the ethical considerations, challenges, and best practices for integrating AI into customer support  </li></ul><div> </div><div><strong>Course Overview</strong>   <br /><br /></div><div>GenAI is revolutionizing how customer service and IT support teams can meaningfully engage with customers.   <br /><br /></div><div>According to Gartner, within the next 1-2 years, 80% of customer service and support organizations are expected to adopt generative AI to boost agent productivity and enhance customer experience.  Already, professionals who can leverage GenAI are in high demand.   <br /><br /></div><div>In this course, you’ll learn to use GenAI to enhance customer interactions and streamline support processes. You’ll explore how to automate responses, generate FAQs and user guides, support multiple languages, and optimize the improve lifecycle using GenAI.   <br /><br /></div><div>Further, you’ll discover how to use AI-driven chatbots for inquiries and knowledge management. Then, you’ll learn how to use GenAI to support tasks like Standard Operating Procedure (SOP) documentation, sentiment analysis, and proactive support through behavioral insights. Finally, you’ll look at ethical considerations, challenges, and best practices for AI integration in customer support.   <br /><br /></div><div>Beyond theory, this course emphasizes <strong>hands-on learning</strong>. You’ll gain practical experience using generative AI tools such as ChatGPT and Claude.ai to craft tailored prompts based on customer needs. Through guided labs, you'll build FAQs, design document templates, develop a chatbot, perform sentiment analysis, and apply AI to problem management and helpdesk optimization.  <br /><br /></div><div> <br /><br /><strong>Syllabus<br /></strong><br /></div><div><strong>Module 0: Welcome </strong></div><ul><li>Video: Course Introduction </li><li>Reading: General Information</li><li>Reading: Learning Objectives and Syllabus</li><li>Reading: Grading Scheme</li><li>Reading: How to Make the Most of this Course</li></ul><div><br /></div><div><strong>Module 1: Generative AI and Customer Support </strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Generative AI in the Customer Support Lifecycle </li><li>Video: Generative AI Tools for Customer Support </li><li>Reading: Real-World Applications of Generative AI in Customer Support</li><li>Video: Ticket Management and Resolution Using Generative AI </li><li>Video: Prompt Engineering for Effective Customer Support </li><li>Lab: Exploring Common Prompts for Generative AI in Customer Support </li><li>Video: Creating FAQs and Knowledge Bases with Generative AI </li><li>Lab: Using Generative AI to Create FAQs</li><li>Video: Training Support Agents with Generative AI Simulations </li><li>Video: Automating Call Centers with Generative AI </li><li>Lab: Creating Document Templates Using Generative AI</li><li>Practice Quiz: Generative AI and Customer Support</li><li>Module 1 Summary: Generative AI and Customer Support</li><li>Module 1 Graded Quiz: Generative AI and Customer Support</li></ul><div><br /></div><div><strong>Module 2: Advanced Concepts in Generative AI for Customer Support </strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Build a Basic Chatbot </li><li>Lab: Using Chatbots for Product Inquiries</li><li>Video: Sentiment Analysis Using Generative AI </li><li>Lab: Performing Sentiment Analysis Using GenAI</li><li>Video: Generative AI to Create SOPs </li><li>Video: Limitations and Practical Considerations of Generative AI </li><li>Video: Ethical Considerations for Using Generative AI in Customer Support </li><li>Video: Responsible Use of Generative AI in Customer Support </li><li>Practice Quiz: Advanced Concepts in Generative AI for Customer Support</li><li>Reading: Module 2 Summary: Advanced Concepts in Generative AI for Customer Support</li><li>Module 2 Graded Quiz: Advanced Concepts in Generative AI for Customer Support</li></ul><div><br /></div><div><strong>Module 3: Generative AI for Managers, Final Project, and Final Exam</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Generative AI for Customer Support Managers and Executives </li><li>Video: Data Analytics and Reports Using Generative AI </li><li>Lab: Data Analytics for Customer Support Using Generative AI</li><li>Video: Adopting Generative AI in an Organization for Customer Support </li><li>Readings: End-to-End Solutions for Customer Support with Generative AI</li><li>Practice Quiz: Generative AI for Managers and Executives</li><li>Final Project: Modernizing Health Insurance Support Operations Using Generative AI</li><li>Final Exam: Generative AI Skills for Customer Support Professionals</li></ul><div><br /></div><div><strong>Module 4: Course Wrap-Up</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Course Wrap-Up </li><li>Reading: Glossary: Generative AI Skills for Customer Support Professionals</li><li>Cheat Sheet: Prompts for Common Use Cases in Customer Support</li><li>Congratulations and Next Steps </li><li>Course Team and Acknowledgment</li></ul><div><br /></div><div><strong>Course Rating and Feedback</strong></div><ul><li>Course Rating and Feedback</li></ul><div><br /></div><div><strong>Recommended Background:</strong><br />The course is designed for current or aspiring professionals in customer support or IT support. A basic understanding of customer support principles and a foundational understanding of generative AI is recommended.   </div>
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Generative AI Skills for Customer Support Professionals

 Build the hands-on GenAI skills businesses need to automate support tasks, enhance customer interactions, and optimize service operations.

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  <div>Hello, and welcome to the <strong>Generative AI for Java and Spring Development </strong>course. <br /><br /></div><div>This course is designed for Java and Spring developers looking to expand their expertise with generative AI. You’ll gain the knowledge and skills to leverage Java and Spring to design, implement, test, and deploy AI applications. You will explore how generative AI can help you build better, more useful applications with the programming language you’re already familiar with.<br /><br /></div><div>This course is part of the <a href="https://www.coursera.org/specializations/generative-ai-for-java-and-spring-developer"><strong>Generative AI for Java and Spring Developers specialization</strong></a><strong>, </strong>designed to provide you with the practical skills and knowledge to excel in program management.<br /><br /></div><h1>Course Syllabus</h1><div>Module 1: AI Fundamentals with Java</div><ul><li>Lesson 0: Welcome to the Course</li><li>Lesson 1: Getting Started with AI in Java</li><li>Lesson 2: Introduction to Java AI Libraries and Implementation</li><li>Lesson 3:  Glossary and Graded Quiz </li></ul><div>Key Topics in Module 1</div><ul><li>AI Fundamentals and Java</li><li>Java Environment Setup for AI</li><li>Java AI Libraries Overview</li><li>AI Algorithm Implementation</li><li>Neural Networks with Deeplearning4j</li><li>Sentiment Analysis Applications</li><li>Image Processing Basics</li><li>Image Recognition Implementation</li></ul><div>Module 2: Spring AI Integration</div><ul><li>Lesson 1:  SpringAI Integration</li><li>Lesson 2: Building AI Applications with Spring</li><li>Lesson 3:  Glossary and Graded Quiz  </li></ul><div>Key Topics in Module 2:</div><ul><li>Overview of Spring AI and its integration with the Spring ecosystem</li><li>Spring AI Architecture and Components</li><li>Spring AI's abstraction layers and design patterns</li><li>Configuring Spring AI projects</li><li>RESTful API design for AI services</li><li>Basic recommendation algorithms with Spring AI</li><li>Working with language models in Spring AI</li><li>Implementing text generation features</li><li>Testing Strategies for AI Applications</li><li>Common issues in Spring AI applications</li><li>Debugging tools and techniques</li><li>Deploying Spring AI Applications</li></ul><div>Module 3: Final Project, Final Assessment, and Course Wrap-Up</div><ul><li>Lesson 1: Final Project</li><li>Lesson 2: Final Graded Quiz and Course Wrap-Up</li></ul><div><br /></div><h1><strong>Prerequisites</strong></h1><div>This course is recommended for developers looking to level-up their development careers using generative AI. Basic Java programming and AI knowledge is required. We encourage you to complete a program similar to one of the following if you do not have Generative AI experience:</div><div><br /></div><ol><li><a href="https://www.coursera.org/learn/generative-ai-introduction-and-applications">Generative AI: Introduction and Applications</a></li><li><a href="https://www.coursera.org/learn/generative-ai-prompt-engineering-for-everyone?">Generative AI: Prompt Engineering Basics</a></li><li><a href="https://www.coursera.org/learn/generative-ai-elevate-software-development-career?specialization=generative-ai-for-software-developers">Generative AI: Elevate your Software Development Career</a></li></ol><div><br /></div><h1>Learning <strong>Objectives</strong></h1><div>After completing this course, you will be able to:</div><ul><li>Explain AI concepts and set up a Java dev environment optimized for developing AI-powered applications with Java.</li><li>Build AI application features using Java and implement neural networks using Deeplearning4j for NLP, image recognition, and recommendation tasks.</li><li>Design and integrate AI service layers, RESTful APIs, and components into Spring applications using best practices.</li><li>Test, debug, deploy, and manage Spring AI apps with proper configuration, logging, and error handling strategies.</li></ul><div><br /></div>
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<div>Kickstart your career in the high-demand field of full-stack development. In this program, you’ll master essential technologies like React, JavaScript, and Node.js—and become job-ready in under 4 months, with no prior programming experience required.<br><br>After completing this professional certificate, you will be able to:&nbsp;<br><br></div><ul><li>Identify and describe the core languages, frameworks, and tools used in full-stack JavaScript development (e.g., React, Node.js, Express, MongoDB).</li><li>Develop responsive front-end applications using HTML, CSS, JavaScript, and React to create dynamic user interfaces.</li><li>Design and deploy scalable cloud-native back-end services using Node.js, NoSQL databases, containers, microservices, and serverless architectures.</li><li>Compare different DevOps strategies and select appropriate CI/CD tools to automate software deployment pipelines.</li><li>Build a full-stack web application by integrating front-end and back-end components with RESTful APIs or GraphQL.</li><li>Apply Agile methodologies (e.g., Scrum, Kanban) to iteratively develop, test, and refine software projects in a collaborative environment.</li></ul><div><br>A full-stack JavaScript developer designs, builds, and maintains both the front-end (client-side) and back-end (server-side) of web applications using JavaScript libraries and frameworks.</div><div>In this program, you’ll learn to build, deploy, test, run, and manage cloud-native full-stack applications. Technologies covered include HTML, CSS, GitHub, JavaScript, Node.js, Express, React, DevOps, Containers, Docker, Kubernetes, NoSQL databases, Microservices, Serverless computing, and more.&nbsp;<br><br></div><div>You’ll build multiple real-world applications using front-end and back-end frameworks and deploy them using industry best practices. The final course includes exclusive interview prep tips and career support resources to help you land your dream job as a full stack developer.<br><br></div><div>By completing the program, you’ll have:</div><ul><li>A professional portfolio of projects to showcase your skills</li><li>An IBM Professional Certificate &amp; digital badge to validate your expertise</li><li>The confidence and technical proficiency to excel in interviews.</li></ul><div><br>Hands-On Learning Projects:<br><br></div><div>Throughout the program, you’ll apply your skills through practical labs and projects, including:<br><br></div><ul><li>Building a personal portfolio site with HTML, CSS, and JavaScript</li><li>Publishing open-source projects on GitHub</li><li>Developing a travel recommendation app using JavaScript APIs</li><li>Designing a budget tracker with React for the front-end</li><li>Creating a book review API with Node.js, Express, and a NoSQL database</li><li>Deploying a cloud-based guestbook app with rolling updates</li><li>Integrating a React front-end with a MongoDB back-end</li><li>Crafting a polished full-stack developer resume and portfolio</li></ul><div><br>Gain real-world experience and stand out in the competitive job market with industry-aligned projects and IBM-backed credentials.<br><br>This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.<br><br>No prior programming experience is necessary to get started.</div>

IBM Full Stack Developer JavaScript Professional Certificate

Launch your Full-Stack Developer career with JavaScript. Build the skills and hands-on experience to get job-ready in under four months. No prior programming experience required.

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  <h1>Project Demo and Introduction</h1><div>
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</div><div>In this project, you will develop a browser extension that uses toxicity detection to analyze and filter text on a webpage. This tool will provide a simple solution to the widespread hate and negativity that permeates the Internet. The project will use a pre-trained BERT model (ToxicBERT) and an LLM (Meta's Llama 3) for text processing. The BERT model will detect toxicity past a certain threshold and the LLM will transform the text if that threshold is exceeded. Text processing will be integrated into a FastAPI app, making it easy to interface with via the JavaScript extension. Additionally, there will be steps for testing and deployment to use the extension on your local device. You will be guided through the full software development cycle, from design to build to launch. This comprehensive project will not only strengthen your programming skills but also provide hands-on experience with deploying AI in a practical application. By the end, you’ll have a working extension that leverages the power of natural language processing to address a common problem on the Internet.</div><div><br /></div><h1>A Look at the Project Ahead</h1><div>By the end of this project you will:</div><ul><li>Understand how BERT and LLMs process language in a nutshell</li><li>Use a pre-trained BERT model to detect negativity in web-scraped content</li><li>Prompt an LLM (Llama 3) to transform the text into a positive alternative</li><li>Build a FastAPI backend to wrap your text-processing pipeline</li><li>Build a simple JavaScript extension to scrape and modify the DOM</li><li>Test and debug your API within the CloudIDE</li><li>(Optional) Load and test the extension locally in your browser</li></ul><div><br /></div><h1>What You'll Need</h1><ul><li>A solid foundation in JavaScript, Web APIs and Web Development<ul><li>Familiarity with using the console to log and debug</li></ul></li><li>A basic understanding of Python classes and Object Oriented Programming</li><li>A basic familiarity with APIs and how they are interfaced</li><li>A basic understanding of Git actions and commands</li><li>(Optional) Firefox or Chrome browser for testing</li></ul>
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Build a Negativity Filtering Web Extension with GenAI

Enhance your web development and JavaScript skills by building a smart browser extension that utilizes the latest generative AI techniques. In this beginner friendly project you'll build a browser extension powered by LLMs and BERT to transform negative content. Through hands-on experience, you’ll learn how these language models process human text and discover their typical use cases. This project is the ideal launchpad for developers looking to integrate AI into their applications. Enroll now to expand your technical skills by building a tool that improves online experiences.

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  <div>In this course, you’ll learn how to use GenAI to boost efficiency, product value, and strategic alignment. </div><div> </div><div>You’ll explore how AI informs product strategy through market trend analysis, sentiment insights, and competitive benchmarking. You’ll get hands-on using GenAI tools to generate user stories, assess features, and prioritize the backlog. Plus, you’ll learn how to use AI to enhance stakeholder communication and alignment throughout development.  <br /><br /></div><div>You’ll also look at ethical AI practices such as identifying risks, addressing bias, and promoting responsible adoption in product management.  <br /><br /></div><div>Throughout, you’ll build a strong, practical understanding of how to use GenAI tools like Gemini, ChatGPT, and Copilot in hands-on labs. Plus, in a guided project, you’ll use these tools to create essential product artifacts and deliverables across the product lifecycle.<br /><br /></div><div><br /><br /></div><h1>Course Syllabus</h1><div>Tell your audience what they can expect to learn. Better yet, tell them what they will be able to do as a result of completing your course:<br /><br /><strong>Module 1</strong>: Integrating AI into Product Ownership  </div><ul><li><strong>Lesson 0:</strong> Welcome to the Course  </li><li><strong>Lesson 1: </strong>AI’s Role in Modern Product Ownership  </li><li><strong>Lesson 2:</strong> AI-Driven Requirements and Stakeholder Engagement  </li><li><strong>Lesson 3:</strong> Summary and Assessment  </li></ul><div>  </div><div><strong>Module 2:</strong> AI-Driven End-to-End Sprint Management and Ethical Considerations  </div><ul><li><strong>Lesson 1:</strong> Enhancing Sprint Planning and Execution with AI  </li><li><strong>Lesson 2:</strong> Ethical Considerations in AI-Driven Product Ownership </li><li><strong>Lesson 3:</strong> Summary and Assessment  </li></ul><div>  </div><div><strong>Module 3</strong>: Guided Project, Final Assessment, and Course Wrap-Up </div><ul><li><strong>Lesson 1:</strong> Project: Guided AI Program Case Study  </li><li><strong>Lesson 2:</strong> Final Course Assessment  </li><li><strong>Lesson 3:</strong> Course Wrap-Up </li></ul><div><br /></div><div><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>A foundational understanding of product ownership, AI concepts, and generative AI fundamentals is recommended. </div>
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Generative AI: Revolutionizing the Product Owner Role

Product Owners who can leverage generative AI have a real competitive edge. It’s a powerful tool that enables them to make informed decisions quickly, improve backlog management efficiency, and enhance stakeholder collaboration.   

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  <div>A Jakarta EE application consists of modules that work together as one entity. An enterprise archive (EAR) is a wrapper for a Jakarta EE application, which consists of web archive (WAR) and Java archive (JAR) files. To deploy or distribute the Jakarta EE application into new environments, all the modules and resources must first be packaged into an EAR file.</div><div><br />In this guide, you will learn how to:</div><ul><li>establish a dependency between a web module and a Java library module,</li><li>use Gradle to package the WAR file and the JAR file into an EAR file so that you can run and test the application on Open Liberty, and</li><li>use the Liberty Gradle plug-in to develop a multi-module application in <a href="https://openliberty.io/docs/latest/development-mode.html#_run_multi_module_gradle_projects_in_dev_mode">dev mode</a> without having to prebuild the JAR and WAR files. In dev mode, your changes are automatically picked up by the running Liberty instance.</li></ul><div>You will build a unit converter application that converts heights from centimeters into feet and inches. The application prompts the user to enter a height value in centimeters. Then, the application processes the input by using functions that are found in the JAR file to return the height value in imperial units.</div>
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Creating a multi-module application with Gradle

You will learn how to build an application with multiple modules with Gradle and Open Liberty.

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  <div>Metasploit is one of the best-known and most used cybersecurity technologies for penetration testing (Cyber Security News). This short course gives you the job-ready skills in exploitation techniques and penetration testing using Metasploit employers are looking for.  <br /><br /></div><div>During the course, you’ll explore Metasploit’s core functionalities, gaining valuable hands-on experience in exercises that cover real-world exploitation scenarios, including network, system, and web application attacks. Plus, you’ll dive into post-exploitation tactics, persistence techniques, and attack simulations, building the skills you need for both ethical hacking and red teaming.  <br /><br />By the end of the course, you’ll be able to conduct advanced penetration tests, execute sophisticated exploits, and understand the tactics used by attackers to compromise systems. Plus, you’ll be able to identify vulnerabilities and implement effective countermeasures to defend against these threats.  <br /><br /></div><h1>Course Syllabus</h1><ul><li><strong>Module 1: Metasploit Essentials and Exploit Development: </strong>This module will introduce you to the Metasploit Framework, its installation, interface, and the foundational concepts of exploitation. </li><li><strong>Module 2: Exploit Development and Auxiliary Module Usage: </strong>This module explores auxiliary modules, session handling, and exploit development. </li><li><strong>Module 3: Post-exploitation and Attack Simulations: </strong>This module explores techniques attackers use after compromising a system, including privilege escalation, persistence mechanisms, evasion techniques, and network attack simulations.</li><li><strong>Module 4: Web and Social Engineering Attacks: </strong>This module covers exploitation techniques targeting web applications and human vulnerabilities. </li><li><strong>Module 5: Final Project: Simulated Penetration Test Using Metasploit: </strong>This module serves as the capstone for the course. In it, learners will apply all acquired skills to conduct a comprehensive penetration test using Metasploit. </li></ul><h1>Prerequisites</h1><div>To take this course, you need to:</div><ul><li>Have completed the Course: <a href="https://www.coursera.org/learn/ethical-hacking-with-kali-linux">Ethical Hacking with Kali Linux</a></li><li>Have a basic understanding of cybersecurity concepts and penetration testing methodologies</li><li>Have familiarity with Linux and Windows environments</li><li>Have exposure to networking fundamentals</li></ul>
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Exploitation and Penetration Testing with Metasploit

Metasploit is one of the best-known and most used technologies for cyber security (Cyber Security News). This short course gives you the job-ready skills in exploitation techniques and penetration testing using Metasploit employers are looking for.  During the course, you’ll explore Metasploit’s core functionalities, gaining valuable hands-on experience in exercises that cover real-world exploitation scenarios, including network, system, and web application attacks. Plus, you’ll dive into post-exploitation tactics, persistence techniques, and attack simulations.

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  <div>Gain demonstrable Java development experience you can showcase to employers with this IBM capstone project, designed to put your job-ready programming skills to work in a real-world scenario. <br /><br /></div><div>This hands-on project challenges you to implement application architecture and software development concepts and techniques as you move a clinic’s administration from paper-based workflows to an online Smart Clinic Management System.   <br /><br />During the project, you’ll put key skills into practice, including requirements gathering with an Agile framework, SQL and NoSQL database design, and architecting an MVC-based Spring Boot application with Java annotations and validations. Plus, you’ll build a frontend with HTML, CSS, and JavaScript for admins, doctors, and patients.  <br /><br />As you progress, you’ll also design key artifacts, including user stories, an architecture document, a database design document, and CI/CD plans. Then you’ll submit a public repository with all the code and the architecture design document for evaluation.  <br /><br />If you’re an aspiring software developer who wants a portfolio project that demonstrates your job-ready Java skills to prospective employers, enroll today!<br /><br />It is recommended that you complete the following courses: <br /><br />• Introduction to Software Engineering <br />• Java Programming for Beginners  <br />• Getting Started with Git and GitHub <br />• Introduction to HTML, CSS, &amp; JavaScript  <br />• Object Oriented Programming in Java <br />• Cloud Native, Microservices, Containers, and Agile <br />• Spring Framework for Java Development  <br />• Java Development with Databases<br /><br /></div><h1>Course Syllabus</h1><div><strong><br />Module 1: Project Overview and Requirements Gathering<br /></strong><br /></div><div><strong>Description: </strong>This module introduces the capstone case study and outlines key prerequisites. You’ll explore technical design and user story concepts, define architecture, identify microservices, and set up your development environment. </div><div><strong><br />Module 2: Database Designs and JPA Models</strong></div><div><strong><br />Description: </strong>In this module, you’ll design MySQL and NoSQL schemas for a healthcare portal, define keys and relationships, and create JPA models for patient, doctor, appointment, and admin. </div><div><strong><br />Module 3: Sample Data and Stored Procedures<br /></strong><br /></div><div><strong>Description: </strong>This module covers setting up the initial MySQL database and adding sample data to SQL and NoSQL databases. </div><div><strong><br />Module 4: Frontend and MVC</strong></div><div><strong><br />Description: </strong>In this module, you’ll build the MVC structure for login screens in the Smart Clinic Management app using Spring Boot and Thymeleaf. <br /><br /></div><div><strong>Module 5: Dockerize Spring Boot Application</strong></div><div><strong><br />Description: </strong>This module covers containerizing the frontend and backend of the Smart Clinic Management System using Docker. </div><div><strong><br />Module 6: Final Submission and Course Wrap-up</strong></div><div><strong><br />Description: </strong>In this final module, you’ll submit the working GitHub repository link(s) as deliverables for the Final Submission and AI-grading. </div><div><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div><strong><br />Prerequisites</strong></div><div>This course is ideal for aspiring software developers seeking to demonstrate job-ready Java skills or enhance their in-demand skills to power their careers in modern Java-based software engineering. Before you begin this course, it is essential that you complete all the preceding courses in the <br /><a href="https://www.coursera.org/professional-certificates/java-developer?"><strong>IBM Java Developer Professional Certificate:</strong></a></div><div><br /></div><ul><li><a href="https://www.coursera.org/learn/introduction-to-software-engineering?">Introduction to Software Engineering</a></li><li><a href="https://www.coursera.org/learn/java-for-programming-beginners?specialization=java-developer">Java Programming for Beginners</a></li><li><a href="https://www.coursera.org/learn/getting-started-with-git-and-github">Getting Started with Git and GitHub</a></li><li><a href="https://www.coursera.org/learn/introduction-html-css-javascript">Introduction to HTML, CSS, &amp; JavaScript</a></li><li><a href="https://www.coursera.org/learn/object-oriented-program-in-java?specialization=java-developer">Object Oriented Programming in Java</a></li><li><a href="https://www.coursera.org/learn/cloud-native-microservices-containers-devops-agile?specialization=java-developer">Cloud Native, Microservices, Containers, and Agile</a></li><li><a href="https://www.coursera.org/learn/spring-framework-for-java-development?specialization=java-developer">Spring Framework for Java Development</a></li><li><a href="https://www.coursera.org/learn/java-development-with-databases?specialization=java-developer">Java Development with Databases</a></li></ul>
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Java Development Capstone Project

Gain hands-on Java development experience that you can confidently present to employers through this IBM capstone project. It's specifically designed to apply your job-ready programming skills in a practical, real-world setting.

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  <div>Imagine analyzing bike rental data and discovering that your model predicts accurately on sunny days but fails completely during rainy rush hours. Traditional feature importance methods might tell you that both "weather" and "time" matter, but they miss how these factors work together. This is the power of understanding feature interactions—the collaborative effects that create patterns beyond what individual features reveal.</div><div><br />In this hands-on lab, you'll master Friedman's H-statistic, a powerful technique for quantifying and visualizing how features collaborate in your model's decision-making process.</div><div><br /></div><h1><strong>Project Overview</strong></h1><div>This lab teaches you to detect and measure feature interactions through a comprehensive workflow:</div><div>1️⃣ <strong>Synthetic Data Exploration</strong> - Generate datasets with controlled interaction effects to understand how the H-statistic detects relationship patterns<br />2️⃣ <strong>Visualization Techniques</strong> - Create PDP and ICE plots to visually identify where features influence each other<br />3️⃣ <strong>Interaction Quantification</strong> - Calculate pairwise H-statistics to measure exactly how strongly features collaborate<br />4️⃣ <strong>Real-World Application</strong> - Apply these techniques to the UCI Bike Sharing dataset to uncover meaningful interactions</div><div><br />By implementing the H-statistic methodology, you'll develop a deeper understanding of model behavior and reveal insights that traditional feature importance measures miss completely.</div><div><br /></div><h1><strong>What You'll Learn</strong></h1><div>By completing this lab, you will:</div><ul><li>Generate controlled datasets to understand how interactions manifest in data</li><li>Build tree-based models and analyze their interaction capabilities</li><li>Visualize feature relationships using Partial Dependence and ICE plots</li><li>Calculate and interpret H-statistics to quantify interaction strength</li><li>Identify which feature pairs most strongly influence predictions</li><li>Apply your knowledge to enhance model interpretability in real-world data</li></ul><div><br /></div><h1><strong>Who Should Do This Lab</strong></h1><div>This project is ideal for:</div><ul><li>Data scientists looking to go beyond basic feature importance analysis</li><li>ML practitioners seeking deeper model interpretability</li><li>Analysts who want to explain "why" models make certain predictions</li><li>Anyone interested in advanced feature engineering techniques</li></ul><div>No advanced statistical expertise required—basic machine learning knowledge and curiosity about model interpretation are all you need.</div><div><br /></div><h1><strong>What You Need</strong></h1><div>✅ A browser to access the lab environment<br />✅ Basic Python knowledge (understanding functions and data structures)<br />✅ Familiarity with machine learning concepts (decision trees, feature importance)</div><div><br />By the end of this project, you'll have mastered a powerful technique that transforms how you interpret machine learning models—enabling you to uncover hidden patterns that drive predictions and build more accurate models through informed feature engineering.</div>
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Master H-Statistic: Uncover & Visualize Feature Interactions

Uncover hidden relationships that traditional feature importance tools miss by learning to analyze feature interactions using the H-statistic. In this hands-on project, you'll visualize joint effects with PDP and ICE plots, and apply interaction analysis to real-world bike sharing data. Measure interaction strength in decision trees and random forests, interpret pairwise and one-vs-all H-statistics, and compare additive vs. interactive model behavior. Gain practical skills to enhance model interpretability and guide feature engineering. Build skills that boost both model insight & performance.

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  <div><strong>Imagine understanding why your model makes predictions</strong> beyond simple feature importance. What if you could identify exactly how features collaborate to influence outcomes? This is the power of <strong>feature interaction analysis using the H-statistic</strong>.</div><div><br />In this hands-on lab, you'll uncover the hidden patterns in how variables work together to affect predictions—transforming how you interpret machine learning models and engineer more effective features.<br /><br /></div><h1>Project Overview</h1><div>This lab teaches you to quantify and visualize feature interactions in a real-world bike sharing prediction scenario:</div><div>1️⃣ <strong>Feature Interaction Fundamentals</strong> - Learn why combinations of features (like time of day × workday status) can create effects that individual features alone don't capture</div><div>2️⃣ <strong>H-Statistic Calculation</strong> - Master techniques for measuring exactly how strongly features interact, both in pairs and overall</div><div>3️⃣ <strong>Practical Application</strong> - Apply these techniques to discover which feature combinations most strongly influence bike rental patterns</div><div>4️⃣ <strong>Visualization &amp; Interpretation</strong> - Translate statistical findings into actionable insights using partial dependence plots</div><div>By measuring interactions with the H-statistic calculator, you'll detect patterns like how wind affects bike rentals differently on holidays versus workdays—insights that traditional feature importance measures completely miss.<br /><br /></div><h1>What You'll Learn</h1><div>By completing this lab, you will:</div><ul><li>Understand the mathematics behind the H-statistic and how it quantifies interaction strength</li><li>Calculate both pairwise (Hij) and one-vs-all (Hj) interaction statistics</li><li>Identify the strongest feature interactions in real-world data</li><li>Visualize how features jointly influence predictions using partial dependence plots</li><li>Apply insights to improve feature engineering and model interpretation</li></ul><div><br /></div><h1>Who Should Do This Lab</h1><div>This project is ideal for:</div><ul><li><strong>Data scientists</strong> seeking deeper insights from their models</li><li><strong>ML engineers</strong> wanting to improve feature engineering through interaction analysis</li><li><strong>Analysts</strong> needing to explain complex model behavior to stakeholders</li><li><strong>AI enthusiasts</strong> interested in advanced model interpretation techniques</li></ul><div>No advanced statistics expertise required—basic machine learning knowledge and curiosity about model behavior are all you need.<br /><br /></div><h1>What You Need</h1><div>✅ <strong>A browser</strong> to access the lab environment<br />✅ <strong>Basic Python knowledge</strong> (understanding functions and data structures)<br />✅ <strong>Familiarity with machine learning concepts</strong> (decision trees, feature importance)</div><div><br />By the end of this project, you'll have mastered a powerful technique for uncovering the collaborative effects of features—enabling you to build more accurate models and explain their behaviour with unprecedented clarity.</div>
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Exploring Feature Interactions using H-Statistic

Discover hidden relationships in machine learning models with H-statistic analysis, revealing how features work together beyond their individual effects. When buying a car, colour and engine type matter but it's the red sports car with a turbo engine that really sells. In this project, learn to quantify high impact feature combinations and interpret how they influence predictions. Train decision tree models, calculate pairwise and one-vs-all interaction metrics, and analyze which feature combinations (such as holiday×windspeed) most strongly affect bike rental patterns.

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  <div>In today's rapidly evolving technological landscape, mastering fundamental AI concepts like <strong>Retrieval-Augmented Generation (RAG) </strong>and<strong> Agentic AI </strong>is no longer optional—it's essential for any aspiring software engineer or machine learning engineer trying to get their foot in the door. Businesses face challenges responding to clients' queries: teams spending endless hours answering repetitive questions that waste their valuable time. This project offers you a unique opportunity to build a customized, efficient chatbot that <strong>solves such real-world problems</strong>, allowing staff to focus on true value-adding tasks. By completing this guided project, you'll gain practical, hands-on experience in building intelligent systems that can revolutionize customer interactions and streamline operations.<br /><br /></div><h1>Who Should Enroll</h1><ul><li>Anyone interested in learning about AI agents and fundamental machine learning concepts like Retrieval-Augmented Generation (RAG)</li><li>Those looking to build specialized chatbots for domain-specific applications such as customer service, technical support, or other interactive use cases</li><li>Developers and tech enthusiasts seeking to gain practical experience with in-demand AI technologies</li></ul><div><br /></div><h1>Why Enroll</h1><div>This hands-on project delivers essential, high-demand skills that define today's technology sector. In just 30 minutes, you'll gain practical experience building AI solutions through clear visual demonstrations and accessible explanations. The course accommodates both newcomers to AI concepts and experienced developers seeking to solidify their understanding of these foundational technologies. By the end, you'll have both theoretical knowledge and practical implementation skills that are immediately applicable to real-world projects.</div><div><br /></div><h1>A Look at the Project Ahead</h1><div>Upon completing this 30-minute <strong>beginner-friendly</strong> lab, you will be able to:</div><ul><li>Build a customer service chatbot using CrewAI and LLMs</li><li>Deploy AI agents with specific roles, tools, and knowledge sources</li><li>Extract context from PDFs using Retrieval Augmented Generation (RAG)</li></ul><div><br /></div><div>
      <img src="https://author.skills.network/rails/active_storage/representations/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NDc3ODcsInB1ciI6ImJsb2JfaWQifX0=--5050d8bbe068919c9c2f62d8b0608782dbd70c06/eyJfcmFpbHMiOnsiZGF0YSI6eyJmb3JtYXQiOiJqcGciLCJsb2FkZXIiOnsibiI6LTF9LCJyZXNpemVfdG9fbGltaXQiOlsxMDI0LDc2OF19LCJwdXIiOiJ2YXJpYXRpb24ifX0=--c00de100a38b9e53a1ed92d6c842daa1c865ae13/RAG%20Process.jpg" />

  
      RAG Process
  
<br /><br /></div><h1>What You'll Need</h1><div>You will build your project using the IBM Skills Network Labs, a virtual lab environment that will provide you with everything you need to complete your project. The only thing you need is a modern web browser like Chrome, Firefox, Edge, or Safari. If you would like to showcase your project or deploy it in production for others to use, we recommend deploying it to the IBM Cloud® Code Engine or a similar fully managed serverless or Kubernetes service.<br /><br /><br /></div>
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Build an Agentic RAG Customer Service Chatbot with CrewAI

Build a Retrieval-Augmented Generation (RAG) and Agentic AI chatbot with CrewAI. Apply in-demand skills to solve real-world challenges with AI, leveraging LLMs. Create and orchestrate AI agents, work with databases, and refine prompt engineering for a customer service application used by a restaurant. This hands-on project is a necessity for all software engineers and machine learning engineers seeking to level-up their skills, in only 30-minutes!

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  <div>JavaScript is the one of the world's most widely used programming languages, powering dynamic and interactive web experiences. <br /><br /></div><div>This hands-on course provides a solid foundation in JavaScript for aspiring web, mobile, front-end, back-end, and full-stack developers.<br /><br /></div><div>You'll begin with core programming concepts, including variables, data types, and ES6 features. Through practical exercises, you'll master essential data structures like arrays and objects, while learning to manipulate webpage content using the DOM. You'll write clean, efficient JavaScript code and create interactive web pages with DOM manipulation.<br /><br /></div><div>As you progress, you'll dive deeper into JavaScript's capabilities by:</div><ul><li>Handling errors and debugging your code effectively</li><li>Working with functions, events, and string manipulation</li><li>Creating responsive interfaces through DOM traversal and styling</li><li>Implementing asynchronous operations with AJAX and API calls</li><li>Building real-world projects with confidence</li></ul><div><br /></div><div>The course combines instructional videos with interactive coding labs to reinforce your learning. You'll apply your new skills in a culminating project where you'll build a fully functional, dynamic website from scratch.</div><div>This course equips you with the JavaScript fundamentals needed for modern web development. </div><div>This course is designed for beginners with basic HTML and CSS knowledge. Familiarity with Git is recommended.</div><div><br />After completing this course, you will be able to:</div><ul><li>Explain core JavaScript concepts, including ES6 features, DOM structure, and asynchronous programming principles.</li><li>Apply array methods, string manipulations, and debugging techniques to solve coding challenges.</li><li>Differentiate between value/reference types and compare promise/async-await error-handling strategies.</li><li>Troubleshoot and fix errors in functions, events, and API responses using systematic debugging.</li><li>Modify DOM elements dynamically by traversing nodes and applying styles.</li><li>Build interactive web applications using JavaScript libraries, API data, and responsive navigation systems.</li></ul><h1>Course Syllabus</h1><div><strong><br />Module 1: Introduction to JavaScript Development</strong></div><ul><li>Lesson: Welcome to the Course</li><li>Lesson: Introduction to JavaScript</li><li>Lesson: Introduction to JavaScript Functions and Events</li><li>Lesson: Module 1 Summary, Cheatsheet and Assessment</li></ul><div><strong><br />Module 2: Arrays and Objects in JavaScript</strong></div><ul><li>Lesson: Introduction to Arrays in JavaScript</li><li>Lesson: Introduction to Objects and String in JavaScript</li><li>Lesson: Module 2 Summary, Cheatsheet and Assessment</li></ul><div><strong>Module 3: Working with DOM in JavaScript</strong></div><ul><li>Lesson: Working with DOM</li><li>Lesson: Traversing and Styling of DOM</li><li>Lesson: Module 3 Summary, Cheatsheet and Assessment</li></ul><div><strong>Module 4: JavaScript Async</strong></div><ul><li>Lesson: Requests</li><li>Lesson: Asynchronous Data Retrieval Techniques </li><li>Lesson: Module 4 Summary, Cheatsheet and Assessment</li></ul><div><strong>Module 5: Final Project</strong></div><ul><li>Lesson: Final Project</li><li>Lesson: Course Wrap Up</li></ul><div><br /></div><h1>General Information</h1><div>This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.<br /><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>The following skills are required to be successful with this course: </div><div> </div><ul><li>Basic knowledge of HTML, CSS, JavaScript, and Git</li></ul>
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JavaScript Fundamentals

Master JavaScript Fundamentals! Build dynamic websites with hands-on labs & a final project. This course is perfect for beginners interested in web development! Learn ES6, DOM, AJAX & Async programming.

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  <div>According to recent Stack Overflow surveys, Node.js is used by about 50% of professional developers, making it the most popular server-side technology, while Express ranks as the fourth most popular web framework overall and the top server-side framework. <br /><br /></div><div>This course will equip you with the essential skills to build modern, scalable back-end applications using these industry-standard technologies.<br /><br /></div><div><strong>Hands-On Learning Experience</strong><br /><br /></div><div>Through numerous practical labs and exercises, you'll gain real-world experience:</div><ul><li>Working with Node.js modules and the event-driven architecture</li><li>Handling asynchronous operations using modern JavaScript techniques</li><li>Developing and testing REST APIs</li><li>Implementing Express middleware for enhanced functionality</li></ul><div>The course culminates in a final project where you'll build a complete book review application, giving you tangible evidence of your new skills for your professional portfolio.<br /><br /></div><div>Who Should Take This Course?<br /><br /></div><div>This course is ideal for:</div><ul><li>JavaScript developers looking to expand into back-end development</li><li>Full-stack developers wanting to strengthen their server-side skills</li><li>IT professionals seeking career advancement in web development</li><li>New graduates aiming to establish themselves in the tech industry</li><li>Developers working on cloud-based projects who need server-side expertise</li></ul><div> </div><div>By completing this course, you'll earn a certificate demonstrating your ability to develop server-side applications with Node.js and Express, work with asynchronous operations, implement routing and middleware, manage dependencies with npm, and build RESTful APIs - all highly valuable skills in today's job market.</div><div><br />After completing this course, you will be able to: </div><ul><li>Create robust server-side applications using the Node.js JavaScript runtime environment</li><li>Extend your Node.js applications with powerful third-party packages and frameworks, including Express</li><li>Master NPM (Node Package Manager) to effectively manage dependencies and modules</li><li>Develop asynchronous callback functions and promises to handle complex operations</li><li>Build RESTful APIs and implement all CRUD operations</li><li>Apply routing, middleware, and templating techniques to create efficient web applications</li><li>Implement authentication and session management for secure systems</li></ul><div><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Introduction to Server-Side JavaScript</strong></div><ul><li>Course Introduction: Welcome to Developing Back-End Apps with Node.js &amp; Express•3 minutes</li><li>Welcome</li><li>Course Overview</li><li>What is Back End Development?</li><li>Reading: Back-end and Front-end Development Overview</li><li>Getting Started with Node.js</li><li>Introduction to Node.js</li><li>Expert Viewpoints: Introductory Thoughts on Server-Side JavaScript and Node.js</li><li>Import and Require</li><li>Introduction to Server-Side JavaScript</li><li>Creating a Web Server with Node.js</li><li>Working with Node.js Modules</li><li>Advanced Node.js Modules</li><li>Overview of Node Package Manager</li><li>Hands-on Lab - First Server with Server-Side Java Script</li><li>Module Summary</li><li>Glossary: Introduction to Server-Side JavaScript</li><li>Cheatsheet: Introduction to Server-Side JavaScript</li><li>Practice Quiz</li><li>Graded Quiz</li><li>Discussion: Introduce yourself and why you are interested in back-end development with Node.js &amp; Express</li></ul><div><strong>Module 2: Asynchronous I/O with callback programming</strong></div><ul><li>Asynchronous I/O with Callback Programming</li><li>Creating Callback Functions</li><li>Expert Viewpoints: Using Anonymous Callback Functions in Node.js</li><li>Issues with Callbacks</li><li>Promises</li><li>Hands-on Lab: Promises and Call Back</li><li>Working with JSON</li><li>Expert Viewpoints: Using JSON &amp; JavaScript</li><li>Promises, async/await, and axios requests in Node.js and Express</li><li>Lab: Promises, Async/Await, and Axios Requests in Node.js and Express</li><li>Hands-on Lab - Async Callback Programing</li><li>Module Summary</li><li>Glossary - Asynchronous I/O with Callback Programming</li><li>Cheatsheet - Asynchronous I/O with Callback Programming</li><li>Practice Quiz</li><li>Graded Quiz</li></ul><div><br /></div><div><strong>Module 3: Express Web Application Framework</strong></div><ul><li>Extending Node.js</li><li>Expert Viewpoints: Working with Third-Party Node.js Extensions</li><li>Introduction to Web Frameworks</li><li>Express Web Application Framework</li><li>Your First Express Web Application</li><li>Expert Viewpoints: Working with Back-end JavaScript Frameworks and Express</li><li>Introduction to Middleware &amp; Routers</li><li>Routing, Middleware, and Templating</li><li>Authentication and Authorization in Node.js</li><li>Welcome to Authentication and Authorization in Node.js</li><li>Authentication in Node JS</li><li>HTTP Methods and Rest APIs</li><li>Hands-on Lab: CRUD Operations with Node.js and Express</li><li>Express Best Practices</li><li>Hands-On Lab: Express Server</li><li>Module Summary</li><li>Glossary - Express Web Application Framework</li><li>Cheatsheet - Express Web Application Framework</li><li>Practice Quiz</li><li>Graded Quiz</li></ul><div><br /><strong>Module 4: Final Project</strong></div><ul><li>Practice Project<ul><li>Hands-on Lab: Friends List Application Using Express Server with JWT</li></ul></li><li>Final Project<ul><li>Project Overview: Scenario and Review Criteria</li><li>Project Breakdown</li><li>Hands on Lab: Book Review Application</li><li>Peer Review Assignment</li><li>Module Summary</li></ul></li><li>Course Wrap Up<ul><li>Thanks from the Course Team</li><li>Congrats &amp; Next Steps</li></ul></li></ul><div><br /></div><h1>General Information</h1><div>This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.<br /><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>The following skills are required to be successful with this course: </div><ul><li>Working knowledge of JavaScript and Git is required to succeed in this course.</li></ul>
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Back-End App Development with Node.js and Express

Master back-end development with Node.js & Express! Learn how to build REST APIs, handle async operations, use NPM, and implement authentication, using hands-on labs & a final project. 

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  <div>Developing Back-End Database Applications with Node.js &amp; MongoDB is an intermediate level course that equips developers with comprehensive skills to build secure, scalable database-driven applications. Starting with foundational database concepts, you'll explore both relational and NoSQL paradigms before diving deep into MongoDB's document-based architecture.<br /><br /></div><div>The course provides hands-on experience in setting up MongoDB environments, establishing Node.js connections, and performing data operations including queries and aggregations. You'll master authentication systems by implementing JWT security, secure password storage, and session management while learning to mitigate common vulnerabilities like CSRF attacks.<br /><br /></div><div>Through practical exercises, you'll construct robust RESTful APIs using Express.js, implement CRUD operations, endpoint design, versioning, and pagination. The curriculum covers essential production-grade skills including error handling middleware, request validation, rate limiting, and debugging techniques.<br /><br /></div><div>As you progress, you'll learn deployment strategies and performance optimization for cloud environments, including load balancing techniques. The course culminates in a capstone project where you'll integrate all concepts by building a full-stack application with user authentication, database interactions, and front-end integration - creating a portfolio-ready demonstration of your back-end development expertise.</div><div><br />After completing this course, you will be able to: </div><ul><li>Design and implement a secure RESTful API using Node.js and Express that performs CRUD operations with MongoDB, demonstrating proper endpoint architecture and error handling.</li><li>Evaluate authentication strategies by implementing JWT security, secure password storage, and session management while mitigating common vulnerabilities. </li><li>Perform database operations by constructing MongoDB queries, aggregation pipelines, and proper indexing strategies.</li><li>Develop production-ready applications by integrating request validation, rate limiting, and custom error handling middleware.</li><li>Compare deployment strategies and implement scaling solutions including load balancing for Node.js applications in cloud environments.</li><li>Apply course concepts by building and deploying a full-stack application with authentication, database integration, and frontend connectivity.</li></ul><div><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Introduction to Working with Databases</strong><br /><br /><strong>Welcome</strong></div><ul><li>Course Introduction</li><li>Course Overview</li><li>Helpful Tips for Course Completion</li></ul><div><strong>Introduction to Databases</strong></div><ul><li>Introduction to Data and Databases</li><li>Relational Databases</li><li>Relational Data Concepts</li><li>Non-relational Databases</li><li>Overview of NoSQL</li><li>Characteristics of NoSQL Databases</li><li>Reading: Types of NoSQL Databases</li><li>Getting started with MongoDB</li><li>Activity: Design a Database for a Product Catalog</li><li>Hands-on Lab: Implement a Product Catalog Database on MongoDB</li></ul><div><strong>Module Wrap-up and Quiz</strong></div><ul><li>Practice Assignment: Introduction to Databases</li><li>Graded Quiz: Introduction to Databases</li></ul><div><br /></div><div><strong>Module 2: Working with Node and Databases</strong></div><div><br /><strong>Introduction to working with NoSQL Databases and Node</strong></div><ul><li>Reading: MongoDB: Installation and Setup</li><li>NoSQL Databases with Node</li><li>Hands-on Lab: Connect Node with MongoDB</li><li>Manipulating Data with MongoDB</li><li>Querying Data with MongoDB</li><li>Hands-on Lab: Exploring and Manipulating Data with MongoDB with Node</li><li>Introduction to Authentication and Authorization</li><li>Implementing User Registration and Login Functionality</li><li>Secure Password Storage and Authorization</li><li>Handling User Sessions and Cookies</li><li>Hands-on Lab: Implementing User Registration and Login</li><li>Practice Assignment: Introduction to working with NoSQL Databases and Node</li></ul><div><strong>Module Wrap-up and Quiz</strong></div><ul><li>Module 2 Summary: Working with Node and Databases</li><li>Graded Quiz: Working with Node and Databases</li></ul><div><strong>Module 3: Working with REST APIs and Advanced Node Concepts</strong></div><div><br /><strong>Restful APIs</strong></div><ul><li>Introduction to RESTful APIs</li><li>Building a RESTful API with Express</li><li>Hands-on Lab: Implement RESTful API for GET and POST operation</li><li>Versioning and Pagination in RESTful APIs</li><li>Implementing CRUD Operations in RESTful APIs</li><li>Authentication and Authorization in Node</li><li>Securing RESTful APIs with JWT</li><li>Hands-on Lab: Implementing JWT Authentication in a Customer Portal API</li><li>Hands-on Lab: Create a RESTful API that allows users to perform CRUD operations</li><li>Practice Assignment: RESTful APIs</li></ul><div><strong>Module Wrap-up and Quiz</strong></div><ul><li>Module 3 Summary: Working with REST API’s and advanced Node concepts</li><li>Graded Quiz: Working with REST API’s and advanced Node concepts</li></ul><div><br /></div><div><strong>Module 4: Error Handling and Middleware<br /><br />Error Handling and Middleware</strong></div><ul><li>Introduction to Error Handling in Node</li><li>Custom Error Handling Middleware</li><li>Asynchronous Error Handling in Node</li><li>Hands-on Lab: Implementing Error Handling in Node</li><li>Request Validation and Sanitization</li><li>Rate Limiting and Throttling Requests</li><li>Logging and Debugging Node Applications</li><li>Hands-on Lab: Logging and Debugging Applications using Node and Express</li><li>Hands-on Lab: Implementing custom error handling middleware in an Express app</li></ul><div><strong>Module Wrap-up and Quiz</strong></div><ul><li>Practice Quiz: Error Handling and Middleware</li><li>Module 4 Summary: Advanced development concepts with Node</li><li>Graded Quiz: Error Handling and Middleware</li></ul><div><br /></div><div><strong>Module 5: Scaling and Deploying Applications in Node</strong></div><div><br /><strong>Scaling and Deploying Applications in Node</strong></div><ul><li>File Uploads and Handling in Node</li><li>Deploying Node Applications</li><li>Hands-on Lab: Deploying a Dockerized Node App for Customer Portals</li><li>Best Practices for Backend Development</li><li>Reading: Performance Optimization Techniques</li><li>Scaling Node Applications</li><li>Load Balancing and High Availability</li><li>Hands-on Lab: Deploying a Node app to a cloud platform</li><li>Hands-on Lab: Create a File Upload and Handling App in Node and Express</li></ul><div><strong>Module Wrap-up and Quiz</strong></div><ul><li>Practice Quiz: Scaling and Deploying Applications in Node</li><li>Module 5 Summary: Scaling and Deploying Node Applications</li><li>Graded Quiz: Scaling and Deploying Node Applications</li></ul><div><strong>Module 6: Final Project<br /></strong><br /></div><div><strong>Final Project</strong></div><ul><li>Final Project Overview</li><li>Hands-on Lab: Final Project</li><li>[Optional] Lab: Practice Project</li><li>Peer-Graded Final Project</li><li>Peer-Graded Final Project: Review Your Peers</li></ul><div><strong>Course Wrap-Up</strong></div><ul><li>Congratulations and Next Steps</li><li>Thanks from the Course Team</li></ul><div><br /></div><h1>General Information</h1><div>This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.<br /><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>The following skills are required to be successful with this course: </div><ul><li>Working knowledge of JavaScript</li><li>Working knowledge of Node and Express</li></ul><div><br /><br /></div>
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Developing Back-end Database Applications: Node.js & MongoDB

Master Node.js & MongoDB for Back-end development! Build secure RESTful APIs, implement JWT authentication, perform CRUD operations, and deploy scalable apps. Grow your skills with hands-on labs & a final project!

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  <div>In this capstone project, you will leverage your skills to solve a real-world inspired challenge and craft an effective solution using your expertise in full stack JavaScript development.<br /><br /></div><div>This project gives you the chance to reinforce your JavaScript front-end and back-end abilities. You’ll design web front-ends using HTML and CSS, and make them dynamic and interactive using React. You will develop back-end services to connect with a MongoDB database, and set up CI/CD pipelines—all while following Agile and DevOps methodologies.<br /><br /></div><div>Throughout this capstone, you’ll apply in-demand skills, including:</div><ul><li>Designing an application architecture</li><li>Building a dynamic frontend with HTML, CSS, and the React JavaScript framework</li><li>Integrating backend services like NoSQL databases</li><li>Implementing DevOps practices such as CI/CD pipelines</li><li>Deploying a serverless application on Cloud</li><li>Developing and consuming RESTful microservices</li><li>Hosting the full solution on the cloud using Kubernetes</li></ul><div>By the end of this project, you’ll have a highly functional full-stack application to show potential employers.</div><div>Before beginning, we strongly recommend finishing all courses in the IBM Full Stack Developer – JavaScript – Professional Certificate.<br /><br />In this capstone project, you will: </div><ul><li>Design a full-stack web application architecture using JavaScript, React, Node.js, Express, and MongoDB. </li><li>Develop a dynamic frontend with React and a scalable backend with Node.js, Express, and MongoDB.</li><li>Integrate RESTful APIs and microservices to enable communication between frontend and backend components.</li><li>Implement DevOps best practices by configuring CI/CD pipelines and deploying using containers (Kubernetes) and serverless technologies.</li><li>Apply Agile methodologies by creating user stories, conducting iterative development, and testing.</li><li>Deploy the full-stack application on a cloud platform and optimize performance for real-world use.</li></ul><div><br /></div><h1>Course Syllabus</h1><div>Module 1: Project Introduction, Repository Setup, User Stories and Database Setup</div><ul><li>Lesson 0: Course Introduction</li><li>Lesson 1: Develop user stories</li><li>Lesson 2: Set up MongoDB and populate data</li><li>Lesson 3: Module summary and assessment </li></ul><div>Module 2 : Back-end APIs and Services</div><ul><li>Lesson 1 : Implement listings</li><li>Lesson 2 : Implement the search API</li><li>Lesson 3 : Implement sentiment analysis service</li><li>Lesson 4 : Module summary and assessment </li></ul><div>Module 3 : Front-end Pages</div><ul><li>Lesson 1 : Landing page and main page </li><li>Lesson 2 : Implement the details and search</li><li>Lesson 3 : Module summary and assessment </li></ul><div>Module 4 : Back-end APIs for front-end components</div><ul><li>Lesson 1 : Develop register API and implement</li><li>Lesson 2: Develop login API and implement</li><li>Lesson 3: Develop user profile API and implement</li><li>Lesson 4: Module summary and assessment </li></ul><div>Module 5: CI/CD, Containerize, and Deploy</div><ul><li>Lesson 1: CI/CD with GitHub actions</li><li>Lesson 2: Containerize and deploy the application</li><li>Lesson 3: Module summary and assessment </li></ul><div>Module 6 : Final Project Submission and Peer Review</div><ul><li>Lesson 1 : Submission </li><li>Lesson 2 : Course Wrap Up</li></ul><div> </div><h1>General Information</h1><div>This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.<br /><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>The following skills are required to be successful with this course: </div><ul><li>Software Engineering</li><li>HTML, CSS</li><li>Git and GitHub</li><li>JavaScript </li><li>React</li><li>Node.js and Express</li><li>Cloud Native, DevOps, Agile, and NoSQL</li><li>Containers with Docker, Kubernetes, &amp; OpenShift</li><li>Microservices and Serverless</li><li>MongoDB</li></ul>
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Capstone Project: Full Stack JavaScript

Demonstrate your Full Stack JavaScript development expertise through this Capstone Project! Create front-end components, develop back-end services to connect with a MongoDB database, and set up CI/CD pipelines.

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  <div>With the rise of massive visual datasets and multimodal models like CLIP, we now have powerful tools to understand and organize visual media in entirely new ways. This guided project explores how to use CLIP image embeddings to create an  "flower map"—a visual map of relationships between images of flowers based on their semantic content. Instead of organizing images by filename or metadata, we’ll use deep learning to position similar images close to each other in a low-dimensional space, enabling intuitive and visually meaningful exploration. Whether you're a machine learning enthusiast, a botanist, or simply curious about how machines "see" images, this project offers a creative and practical application of state-of-the-art models for visual understanding.<br /><br /></div><h1><strong>What You'll Learn</strong></h1><div>By the end of this project, you will be able to:</div><ul><li><strong>Compute and explore image embeddings</strong>: Learn how to use the CLIP model to convert flower images into numerical vectors that capture their visual and conceptual features.</li><li><strong>Visualize high-dimensional data</strong>: Apply dimensionality reduction techniques to project embeddings into 2D and create visually engaging plots that reveal clusters and relationships in your image dataset.</li><li><strong>Build a semantic image map</strong>: Construct a visual map where similar images naturally group together, enabling intuitive exploration of large collections without labels or manual categorization.</li></ul><h1><strong>Who Should Enroll</strong></h1><ul><li><strong>Researchers</strong> across disciplines interested in using visual semantic maps to automatically discover patterns in large datasets that would be impossible to detect manually. Scientists studying everything from medical imaging to archaeological artifacts can use these tools to identify clusters, outliers, and relationships that reveal new insights about their subjects.</li><li><strong>Machine Learning Enthusiasts </strong>with a basic to intermediate understanding of ML concepts who want to experiment with powerful pretrained models like CLIP. This project will provide a practical and creative walkthrough of multimodal models and teach useful concepts like embedding generation, dimensionality reduction, and visualization.</li><li><strong>Hobbyists</strong> <strong>of anything</strong>! Whether it's flowers, antique coins, or rocks, a semantic search engine lets hobbyists find specimens by visual similarity rather than keywords - they can upload a photo of an unknown flower or rock and instantly discover similar items in their collection or database.</li></ul><div><br /></div><h1><strong>Why Enroll</strong></h1><div>This project bridges the gap between advanced AI theory and practical application, giving you hands-on experience with one of today's most powerful multimodal models. You'll build genuinely useful personal tools that can organize and search any visual collection, from research datasets to personal photos. The skills you learn—embedding generation, dimensionality reduction, and semantic search—are foundational to modern computer vision and applicable far beyond this flower example. By the end, you'll have both working applications and the knowledge to adapt these techniques to your own visual data challenges.<br /><br /></div><h1><strong>What You'll Need</strong></h1><div>To follow along with this guided project, you should have a basic understanding of Python and some familiarity with libraries like matplotlib and PIL. Experience with Jupyter notebooks will be helpful, but not required. All necessary dependencies and datasets are available in the IBM Skills Network Labs environment. The platform works best with current versions of Chrome, Edge, Firefox, or Safari.</div>
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Build an Image Search Engine with OpenAI's CLIP Embeddings

Learn the fundamentals of building Google's reverse image search. Build your own embeddings-based implementation from scratch using OpenAI's CLIP model. Develop a recommendation system that uses semantic image search with CLIP's multimodal embedding architecture. Discover how to visualize high-dimensional vector spaces with spatial reduction algorithms. By the end, you will have created a beautiful semantic map revealing latent relationships across unlabeled datasets.

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  <div>The demand for systems analysts is consistently strong and growing by double digits (US Bureau of Labor Statistics). If you’re looking to start a career in systems analysis, you have a lot to look forward to.  </div><div><br />This course gives non-technical professionals and business graduates the ideal introduction to the field. In just 4 weeks, you’ll build a solid foundational understanding of the role, responsibilities, and skills required to build a rewarding career in systems analysis.  <br /><br />During the course, you’ll look at key concepts such as system development life cycle (SDLC), requirement gathering, process modeling, and feasibility analysis. You’ll explore methodologies such as Agile and Waterfall and discover essential tools for system documentation and design.   <br /><br />You’ll learn to identify systems issues and consider their impact on business processes. Plus, you’ll enhance your problem-solving, critical thinking, and communication skills, helping you to bridge the gap between business needs and technical solutions in your future career.    <br /><br />If you’re looking to kickoff your journey to becoming the go-to Systems Analyst employers need, get the best start you can and enroll today<br /><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Introduction to Systems Analysis</strong></div><ul><li>Lesson 0: Welcome</li><li>Lesson 1: What is a System</li><li>Lesson 2: Understanding Systems and the Analyst’s Role in Business</li></ul><div><strong>Module 2: The Systems Analyst </strong></div><ul><li>Lesson 1: Introduction to Systems Analyst </li><li>Lesson 2: Career in Systems Analysis </li></ul><div><strong>Module 3: Tools of Systems Analyst</strong></div><ul><li>Lesson 1: Tools of Systems Analyst</li><li>Lesson 2: Applying Systems Analyst Tools in Practice</li></ul><h1><strong>Prerequisites</strong></h1><div>This course is accessible to a wide range of professionals, but having some foundational knowledge can enhance the learning experience. A bachelor’s degree in IT, Computer Science, Business, or related fields is beneficial. Equivalent work experience in IT or business operations can also be considered.<br /><br /></div><div>Understanding of software applications and business systems. Familiarity with databases, networking, or programming is a plus (but not required). Ability to analyze business problems and think logically. Experience in decision-making and process improvement is helpful.<br /><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>This course is accessible to a wide range of professionals, but having some foundational knowledge can enhance the learning experience. A bachelor’s degree in IT, Computer Science, Business, or related fields is beneficial. Equivalent work experience in IT or business operations can also be considered.<br /><br /></div><div>Understanding of software applications and business systems. Familiarity with databases, networking, or programming is a plus (but not required). Ability to analyze business problems and think logically. Experience in decision-making and process improvement is helpful.</div>
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Introduction to Systems Analysis

Designed for aspiring Systems Analysts and Business Systems Analysts, this course intends to equip you with the foundational knowledge and practical skills needed to understand, analyze, and improve information systems within an organization. The course focuses on the key role systems analysts play in connecting business requirements with technological solutions. During this short course, you’ll explore the full scope of the System Development Life Cycle (SDLC), including planning, analysis, design, implementation, and maintenance.

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  <div>If you’re just starting out on your project management career, or extending your skillset to include Scrum and Agile methodologies, a capstone project is an excellent way to showcase your practical experience to a prospective employer. This Capstone for Scrum Masters course is designed for professionals seeking to apply foundational Scrum Master skills to a real-world scenario. It’s ideal for showcasing your team collaboration skills and ability to use project management tools in an interview!  <br /><br /></div><div>During this course, you’ll gain hands-on experience creating essential project documents, facilitating Agile processes, and leading a Scrum team to successful a project outcome.  <br /><br /></div><div>You’ll consolidate your understanding of how to initiate project launches and form effective Scrum teams. You’ll fine-tune your skills in developing working agreements and user stories, curating the product backlog, conducting relative estimation, creating the sprint backlog, generating a burndown chart, and facilitating retrospectives. Plus, as you tackle the challenges, you’ll get access to valuable templates and instructional guidance to help you build a portfolio of artifacts.  <br /><br /></div><div>Once you’ve completed this capstone course, you’ll have a portfolio of examples that show employers you’re fully equipped to lead Scrum projects, manage Agile workflows, and contribute to successful project outcomes.  <br /><br /></div><div>If you’re looking to add valuable practical Scrum Master experience to your resume, ENROLL TODAY and get ready to power up your portfolio in just 3 weeks! <br /><br /></div><div> </div><div><strong>You will learn:</strong> </div><ul><li>Build valuable hands-on experience as a Scrum Master you can showcase to an employer in just 3 weeks.  </li><li>Apply Scrum skills, create project charters, perform Stacey analysis, and identify and prioritize stakeholders with optimal engagement methods. </li><li>Create a working agreement, User Stories, product backlog, and Sprint backlog, analyze risks, and develop an Agile risk register. </li><li>Perform relative estimation for story points, calculate team velocity, develop a Kanban board, and generate a burndown chart. </li><li>Evaluate daily Scrum meeting best practices, prepare for a demo, conduct a retrospective, and discuss Scrum certification opportunities. </li></ul><div> <br /><br /></div><h1>Course Syllabus</h1><div><strong>Welcome </strong> </div><ul><li>Video: Course Introduction </li><li>Reading: General Information </li><li>Reading: Learning Objectives and Syllabus </li><li>Reading: Grading Scheme</li></ul><div><strong>Module 1: Program and Course Introduction </strong> </div><ul><li>Reading: Module 1 Introduction and Learning Objectives </li><li>Module 1 Overview and Activity Requirements </li><li>Video: Review the Contents and Purpose of a Project Charter  </li><li>Video: Review a Product Roadmap </li><li>Video: Case Study: Project Charter and Product Roadmap  </li><li>Video: Stacey Diagramming Method </li><li>Lab: Stacey Analysis </li><li>Reading: Stakeholder Identification and Engagement Methods </li><li>Reading: Project Scenario Team Overview </li><li>Video: Review a Working Agreement </li><li>Lab: Develop a Working Agreement for Your Scrum Team </li><li>Practice Quiz: Module 1: Program and Course Introduction </li><li>Reading: Module 1 Glossary: Program and Course Introduction </li><li>Graded Quiz: Module 1: Program and Course Introduction </li><li>Reading: Module 1 Summary: Program and Course Introduction </li></ul><div><strong>Module 2: Product Backlog and User Story Development </strong> </div><ul><li>Reading: Module 2 Introduction and Learning Objectives </li><li>Reading: Module 2 Overview and Activity Requirements </li><li>Video: User Story and Product Backlog Review </li><li>Video: Product Vision </li><li>Lab: Create User Stories, Product Backlog and Product Vision </li><li>Video: Risk Register and Relative Estimation  </li><li>Lab: Create a Risk Register using Force Field Analysis, Perform Relative Estimation, and Update Product Backlog </li><li>Video: Velocity </li><li>Lab: Calculate Velocity </li><li>Practice Quiz: Module 2: Product Backlog and User Story Development </li><li>Reading: Module 2 Glossary: Product Backlog and User Story Development </li><li>Graded Quiz: Module 2 Product Backlog and User Story Development  </li><li>Reading: Module 2 Summary: Product Backlog and User Story Development </li></ul><div><strong>Module 3: Sprint 1 Planning and Execution </strong> </div><ul><li>Reading: Module 3 Introduction and Learning Objectives </li><li>Reading: Module 3 Overview and Activity Requirement </li><li>Video: Sprint Backlog and Kanban Boards  </li><li>Lab: Create Sprint Backlog, Burndown Chart and Kanban Board </li><li>Reading: Project Scenario Update: What Happened in Sprint 1 </li><li>Video Sprint 1 Demo Review Demo Purpose and Planning </li><li>Lab : Daily Standup and Sprint Demo </li><li>Practice Quiz: Module 3: Sprint 1 Planning and Execution </li><li>Module 3 Glossary: Sprint 1 Backlog Development and the Sprint </li><li>Graded Quiz: Module 3 Sprint 1 Backlog Development and the Sprint </li><li>Reading: Module 3 Summary: Sprint 1 Backlog Development and the Sprint </li></ul><div><strong>Module 4: Sprint Close Out and Analysis </strong> </div><ul><li>Reading: Module 4 Introduction and Learning Objectives </li><li>Reading: Module 4 Overview and Activity Requirements </li><li>Video: Sprint 1 Retrospective Overview </li><li>Lab: Read the demo report </li><li>Reading: Closing Out a Sprint </li><li>Reading: Planning for the Next Sprint </li><li>Lab: Review Sprint 1 and Develop a Game Plan for Sprints 2 and 3 </li><li>Practice Quiz: Module 4: Sprint Close Out and Analysis </li><li>Reading: Module 4 Glossary: Sprint Close Out and Analysis </li><li>Graded Quiz: Module 4 Sprint Close Out and Analysis </li><li>Reading: Module 4 Summary: Sprint Close Out and Analysis </li></ul><div><strong>Module 5: Sprint 3- MVP Launch </strong> </div><ul><li>Reading: Module 5 Introduction and Learning Objectives </li><li>Reading: Module 5 Overview and Activity Requirements </li><li>Video: Sprints 1 and 2 Analysis  </li><li>Lab: Develop a Sprint 3 Game Plan </li><li>Reading: Sprint 3 Complete </li><li>Reading: Planning for the Next Sprint </li><li>Lab: Refine the Product Backlog </li><li>Practice Quiz: Module 5: Sprint 3- MVP Launch </li><li>Reading: Module 5 Glossary: Sprint (MVP Launch) </li><li>Graded Quiz: Module 5 Sprint 3- MVP Launch   </li><li>Reading: Module 5 Summary: Sprint 3- MVP Launch </li></ul><div><strong>Module 6: Final Submission and Evaluation </strong> </div><ul><li>Reading: Module 6 Introduction and Learning Objectives </li><li>Reading: Module 6 Overview and Project Submission Requirements </li><li>Peer Review: Final Project </li></ul><div><strong>Module : Course Wrap-Up  </strong></div><ul><li>Reading: Congratulations from the Team </li><li>Reading: Thanks from the Course Team </li><li>Reading: Copyrights and Trademarks </li><li>Reading: Introduction to the Scrum Master Certification Opportunities </li><li>Bonus Module: Your Personal Portfolio and Job Search Guidan </li><li>Reading: Introduction to Bonus Lesson 3 </li><li>Reading: Explain how to develop a portfolio of Scrum Master artifacts to demonstrate your career readiness </li><li>Video: Personal Portfolio Development </li><li>Video: Resume and Job Search Tips </li><li>Course Rating and Feedback  </li><li>Reading: Feedback </li></ul><div><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>Learners who have completed all prior courses in the IBM IT Scrum Master PC or SkillUp EdTech Scrum Master Specialization. </div><div> </div><div>Upon finishing this Capstone course, you will be fully equipped to lead Scrum projects, manage Agile workflows, and contribute to successful project outcomes with a portfolio that showcases your readiness for advanced Scrum responsibilities. </div>
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Capstone Project for Scrum Masters

Gain valuable hands-on experience as a Scrum Master. Create a portfolio of key deliverables that showcase your skills managing Agile projects and build a resume that catches the eye of an employer.  

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  <div><strong>Course Description:</strong>  </div><div>The <strong>Fundamentals of Digital Marketing</strong> course provides a comprehensive introduction to the core concepts, tools, and strategies of digital marketing. This course serves as the perfect foundation for anyone aspiring to build a career in digital marketing or looking to expand their expertise in the field  </div><div>Designed for aspiring digital marketers and business owners alike, this course equips learners with the knowledge and practical skills to navigate the dynamic world of digital marketing. It covers foundational topics, such as digital marketing strategies, digital channels, digital audiences and key metrics that are being used to evaluate success. Through engaging lessons, hands-on labs, and practical projects, learners will develop the confidence to create data-driven, impactful marketing campaigns that align with business goals and industry standards.  </div><div><strong>Course Objectives:</strong>  </div><div>By the end of this course, learners will be able to:  </div><ol><li><strong>Understand the basics of digital Marketing:</strong> Gain a clear understanding of digital marketing concepts, strategies, and its relevance in the modern business environment.  </li><li><strong>Understand Key Digital Channels:</strong> Understand the various channels that are used in digital marketing, such as SEO, social media, email, PPC, and content marketing, to enhance online presence and drive engagement.  </li><li><strong>Understand Digital Strategy:</strong> Gain a clear understanding of what goes into developing a digital strategy  </li><li><strong>Learn about Digital Audiences:</strong> Understand how digital audiences are identified and the importance of demographic and psychographic profiling for digital campaigns </li><li><strong>Understand Digital Metrics:</strong> Gain an understanding of how digital performance is tracked and evaluated and the importance of ROI in evaluating digital activities.  </li><li><strong>Digital Marketing Prospects:</strong> Understand the growth opportunities in pursuing a career in digital marketing and the earning opportunities for freelancers and small business owners </li><li><strong>Apply Practical Skills through Projects:</strong> Develop hands-on expertise by applying course concepts in real-world scenarios through interactive labs and a final project.  </li></ol><div> </div><div><strong>Module 1- Introduction to Digital Marketing </strong> </div><div><strong>Description</strong>  </div><div>This module introduces you to the foundational concepts and practices in digital marketing. It provides a comprehensive overview of digital marketing, its growth, and its relevance in the modern business landscape. This module empowers you to understand digital marketing's core strategies, channels, and analytics.   </div><div>The module also explores the importance of a digital strategy and its role in business success. You will identify the key components of a digital strategy. By the end of this module, you'll have the knowledge to develop effective digital marketing strategies that align with business objectives. </div><div> </div><div><strong>Learning objectives:</strong>  </div><div>By the end of the module, you will be able to:  </div><ul><li>Explain the basics of digital marketing.  </li><li>Differentiate between digital and traditional marketing.  </li><li>Recognize how digital strategies are developed.  </li><li>Recognize the commonly used digital channels.  </li><li>Apply a digital strategy based on business objectives.  </li><li>Explain the importance of a digital strategy and identify its key components. </li><li>Explain the role of analytics in digital marketing and key digital analytics terms. </li></ul>
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Introduction to Digital Marketing

The Fundamentals of Digital Marketing course provides a comprehensive introduction to the core concepts, tools, and strategies of digital marketing. This course serves as the perfect foundation for anyone aspiring to build a career in digital marketing or looking to expand their expertise in the field  Designed for aspiring digital marketers and business owners alike, this course equips learners with the knowledge and practical skills to navigate the dynamic world of digital marketing. 

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  <div><br />In this course, you will learn about user experience (UX) and user interface (UI) design, including their differences and critical roles in successful products. You'll learn about user-centered design, design thinking, Agile methods, and how UX/UI fits into the software development lifecycle. The course also covers career paths, core skills, key tools such as Figma, and how designers collaborate within teams—giving you a solid foundation to work on real UX/UI projects.<br /><br /></div><div><br />This course is part of the <br /><a href="https://www.coursera.org/professional-certificates/ibm-ui-ux-designer">IBM UI/UX Designer Professional Certificate</a><br />. Other courses in this certificate program include:<br /><a href="https://www.coursera.org/learn/agile-development-and-scrum">Introduction to Agile Development and Scrum</a><br /><a href="https://www.coursera.org/learn/uxui-design-fundamentals-usability-and-visual-principles">UX/UI Design Fundamentals: Usability and Visual Principles</a><br /><a href="https://www.coursera.org/learn/uxui-wireframing-and-prototyping-with-figma">UX/UI Wireframing and Prototyping with Figma </a><br />(Coming soon)<br /><a href="https://www.coursera.org/learn/ux-research-and-information-architecture">UX Research and Information Architecture</a><br /> (Coming soon)<br /><a href="https://www.coursera.org/learn/ux-ui-captsone-project">Capstone Project: Applying UX/UI Design in Real World </a><br />(Coming soon)<br />If you’re interested in building on your skills, feel free to explore the other courses in this certificate program at your own pace.<br /><br /></div><div><strong><br />Prerequisites<br /></strong><br /></div><div>To get the most out of this course, basic computer literacy is needed. No prior degree, programming, or UX/UI experience is required.<br /><br /></div><div><strong>Course Objectives<br /></strong><br /></div><div>After completing this course, you will be able to:<br /><br /></div><ul><li><br />Define UX/UI design, their differences, their significance in user satisfaction, and the role of tools such as Figma in creating effective designs</li><li><br />Identify the role of UX/UI design within the product development process and how it aligns with project goals</li><li><br />Assess various UX/UI career paths, required skills, and the impact of tools and team dynamics in Agile workflows</li></ul><div><strong><br />Course Outline<br /></strong><br /></div><div><br />This course has 4 modules, which are listed below. We encourage you to set aside 2-3 hours each week to successfully complete all modules in 4 weeks. Consistency will best help you achieve your learning goals!<br /><br /></div><div><br />You will derive the maximum benefit from viewing all videos and readings and solidifying that knowledge by completing all of the labs and activities.<br /><br /></div><div><strong><br />Module 1: Understanding UX and UI Design<br /></strong><br /></div><div><br />In this module, you'll learn the foundational concepts of UX and UI design and why they matter in building successful digital products. You'll distinguish between UX and UI, explore how they work together, and observe their impact on user satisfaction and business outcomes. Through real-world examples, you'll see how great design can elevate user experiences and give products a competitive edge. By the end, you'll have a clear grasp of what UX and UI design involve and how they shape modern product development.<br /><br /></div><div><strong><br />Module 2: The Role of UX/UI in Product Design<br /></strong><br /></div><div><br />This module explores how UX/UI design applies across platforms, from websites and mobile apps to IoT devices, AR/VR, voice interfaces, and wearables. You'll learn how UX/UI integrates into the software development lifecycle (SDLC), supporting usability, functionality, and innovation at every stage. By the end, you'll understand how thoughtful design drives better products through iterative development and real-world applications.<br /><br /></div><div><strong><br />Module 3: Exploring Careers in UX/UI Design<br /></strong><br /></div><div><br />This module introduces careers in UX/UI design, covering key roles such as UX Designer, UI Designer, Product Designer, and UX Researcher, along with specializations such as Accessibility and Motion Design. You'll build core skills in wireframing, prototyping, and user research, and gain hands-on experience with tools like Figma. The module also explores team dynamics, solo vs. collaborative work, and the soft skills needed for success. By the end, you'll be equipped with the knowledge and tools to start a career in UX/UI design.</div><div><strong><br />Module 4: Final Project and Course Wrap-Up<br /></strong><br /></div><div><br />In this module, you will complete a final project and will take a final exam to test your knowledge. The module also provides guidance about the next steps after completing this course.<br /><br /></div><div><strong>Tools/Software Used<br /></strong><br /></div><div>In this course, you will use the free version of Figma. The course does not require you to purchase paid versions of tools like Figma to complete any activities. However, if you choose to upgrade to a paid version, you will need to incur the costs.<br /><br /></div><div>Congratulations on taking these steps to further your knowledge and career! Enjoy your UX/UI journey.<br /><br /></div>
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Introduction to UX/UI Design

This course provides a comprehensive overview of user experience (UX) and user interface (UI) design, their differences, and their critical roles in product success. You’ll explore the importance of UX/UI design in product development and key processes like user-centered design, design thinking, and Agile methodologies. You will also gain insight into the software development lifecycle. The course also delves into career paths, essential skills, popular design tools such as Figma, and team dynamics, equipping learners with foundational knowledge to excel in UX/UI design projects. 

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  <div>Successful digital ad campaigns generate $4.33 for every $1 spent (Statista). Marketers with strong digital advertising skills are in high demand! This course gives marketers, small business owners, D2C founders, and freelancers the foundation to run successful digital advertising campaigns.</div><div><br />During this course, you'll explore the core elements of digital advertising—search engine marketing (SEM), keyword search, bidding strategies, and ad grouping. You'll learn techniques for planning and optimizing Google search campaigns. You'll dive into B2B marketing, lead generation, advertising strategies, audience targeting, and ad formats. Plus, you'll look at all major social media platforms, including LinkedIn, Facebook, and Instagram. <br /><br />You'll also learn about shopping campaigns on Google and influencer marketing fundamentals, including selecting, evaluating, and collaborating with influencers effectively. And you will learn about how digital advertising is evolving with generative AI.   <br /><br />Through hands-on labs and real-world applications, you'll gain experience creating and optimizing campaigns using data-driven strategies. You will use tools like Shown.io and Facebook Ad Account to maximize return on investment (ROI).  <br /><br />If you're keen to build high-performing ad campaigns that generate real results, ENROLL today!<br /><br /><strong>What you'll learn</strong></div><ul><li>Build the knowledge and skills you need to run successful digital advertising campaigns in just 4 weeks. No prior experience required</li><li>Conduct keyword research and set up Google Search campaigns that are optimized for better ROI</li><li>Create and manage effective advertising campaigns on LinkedIn, Facebook, and Instagram using platform-specific tools and best practices</li><li>Analyze influencer marketing strategies, including identifying appropriate influencers &amp; evaluating campaign effectiveness through relevant metrics</li></ul><h1><strong>Course Syllabus:</strong></h1><div>This course is divided into four modules. You can complete each module at your own pace, but it’s recommended to set a goal of achieving at least one module per week.<br /><strong><br />Module 1: Fundamentals of Digital Advertising and Search Engine Marketing (SEM)<br />Module 2: B2B Lead Generation and Facebook and Instagram Advertising <br />Module 3: Shopping Campaigns and Influencer Marketing<br />Module 4: Assessment and Final Project<br /></strong><br />The module includes a final project based on the concepts covered in the course. You will refer to the glossary for the important terms used in this course. <br /><br /></div><h1>Prerequisites</h1><div>No prior experience is required in digital marketing. You should have basic computer skills and familiarity with MS Office. It is advantageous to have a fundamental knowledge of marketing concepts.  </div><div><br /></div><h1>Tools/software used</h1><div>In this course, you will use the free or trial versions of WordStream, Shown.io, Facebook Ad Account, and LinkedIn Ad Account. You are not required to add your bank or card details while accessing these tools. However, if you add your bank or card details, you will be responsible for any associated charges.<br /><br /></div>
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Digital Advertising

This course is designed for those who want to start their career or enhance their skills in digital advertising campaigns or build a career in performance marketing.

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  <div>Data scientists, AI researchers, robotics engineers, and others who can use retrieval-augmented generation (RAG) can expect to earn entry-level salaries ranging from USD 93,386 to USD 110,720 annually, with highly experienced AI engineers earning as much as USD 172,468 annually (Source: ZipRecruiter). <br />In this beginner-friendly short course, you’ll begin by exploring RAG fundamentals—learning how RAG enhances information retrieval and user interactions—before building your first RAG pipeline. <br /> Next, you’ll discover how to create user-friendly AI applications using Gradio, gaining experience with moving from project planning to constructing a QA bot that can answer questions using information contained in source documents. <br />Finally, you’ll learn about LlamaIndex, a popular framework for building RAG applications. Moreover, you’ll compare LlamaIndex with LangChain and develop a RAG application using LlamaIndex.  Throughout this course, you’ll engage in interactive labs and leverage multiple LLMs, gaining the skills needed to design, implement, and deploy AI-driven solutions that deliver meaningful, context-aware user experiences. <br /><br />Enroll now to gain valuable RAG skills! <strong><br /></strong><br /></div><h1>Course Learning Objectives </h1><ul><li>Develop a practical understanding of Retrieval-Augmented Generation (RAG) </li><li>Design user-friendly, interactive interfaces for RAG applications using Gradio </li><li>Learn about LlamaIndex, its uses in building RAG applications, and how it contrasts with LangChain</li><li>Build  RAG applications using LangChain and LlamaIndex using Python</li></ul><div> </div><h1>Course Syllabus</h1><div><strong>Module 1: Introduction to RAG<br />Lesson 0: Welcome to the Course</strong></div><ul><li>Video: Course Introduction</li><li>Reading: Course Overview</li><li>Reading: Helpful Tips for Course Completion</li></ul><div><strong>Lesson 1: What is RAG?</strong> </div><ul><li>Video: Why Rag?</li><li>Video: More RAG details</li><li>Reading: What is RAG?</li><li>Lab: Summarize private documents using RAG, LangChain, and LLMs</li><li>Practice Quiz: What is RAG?</li></ul><div><strong>Lesson 2: Module Summary and Evaluation</strong></div><ul><li>Reading: Summary and Highlights: Introduction to RAG</li><li>Reading: Cheatsheet: Introduction to RAG</li><li>Graded Quiz: Introduction to RAG</li><li>Discussion Prompt: Meet and Greet</li></ul><div><br /></div><div><strong>Module 2: Build apps with RAG</strong></div><div><strong>Lesson 1: Create an Interactive RAG Application with a User-Friendly Gradio Interface</strong></div><ul><li>Video: Getting Started with Gradio</li><li>Reading: Introduction to Gradio </li><li>Lab: Set Up a Simple Gradio Interface to Interact with Your Models</li><li>Lab: Construct a QA Bot That Leverages the LangChain and LLM to Answer Questions from Loaded Documents </li><li>Practice Quiz: Building apps with RAG</li></ul><div><strong>Lesson 2: Module Summary and Evaluation</strong></div><ul><li>Reading: Summary and Highlights: Building apps with RAG</li><li>Reading: Cheatsheet: Building apps with RAG</li><li>Graded Quiz: Building apps with RAG</li></ul><div><br /></div><div><strong>Module 3: Building RAG apps with LlamaIndex</strong></div><div><strong>Lesson 1: Application Development with LlamaIndex</strong></div><ul><li>Video: Intro to LlamaIndex: Document Ingestion and Chunking</li><li>Video: Intro to LlamaIndex: From Vector Stores to Query Engines</li><li> Reading: LangChain vs LlamaIndex</li><li>Lab: Build an AI Icebreaker Bot with IBM Granite 3.0 &amp; LlamaIndex</li><li>Practice Quiz: Application Development with LlamaIndex </li></ul><div><strong>Lesson 2: Module Summary and Evaluation</strong></div><ul><li>Reading: Summary and Highlights: Build RAG Apps with LlamaIndex</li><li>Reading: Cheatsheet: Build RAG Apps with LlamaIndex</li><li>Graded Quiz: Build RAG Apps with LlamaIndex</li></ul><div><strong>Lesson 3: Course Wrap Up</strong></div><ul><li>Video: Course Wrap-up </li><li>Reading: Congratulations and Next Steps</li><li>Reading: Team and Acknowledgments</li></ul><div><br /></div><h1><strong>Recommended Background</strong></h1><div>Python programming, familiarity with LangChain, and its use in developing simple generative AI applications </div><div><br /></div>
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Build RAG Applications: Get Started

Explore retrieval-augmented generation (RAG) and its integration with generative models to enhance information retrieval. This course focuses on practical applications, guiding you through building RAG-based projects using LangChain and LlamaIndex. Gain a foundational to intermediate understanding through key concepts and hands-on examples.

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  <div>Get ready to power up your resume with the GenAI development skills employers need. During this course you’ll explore core prompt engineering strategies—like in-context learning and chain-of-thought—and create and manage robust prompt templates. Plus, you’ll follow best practices to handle common errors and experiment with different LLMs and configurations to strengthen your outputs.<br /><br />You’ll then dive deeper into LangChain, mastering chains, tools, and agents to create smarter, more responsive applications. Through interactive labs, you’ll build a complete generative AI app using Python that accepts user input and processes it through your backend prompt logic. Plus, you’ll explore web-based interfaces using tools like Flask and Gradio, developing real-time user experiences powered by LLMs.<br /><br />By the end, you’ll have the job-ready skills and demonstrable practical experience employers look for to design and implement full-stack GenAI apps that solve real-world problems. Sound good? Enroll today!<br /><br /></div><h1>Course Learning Objectives</h1><div>After completing this course, you will be able to:</div><ul><li>Master the basics of  GenAI and the LangChain framework, focusing on how prompt engineering and in-context learning to enhance AI interactions </li><li>Apply prompt templates, chains, and agents to create flexible and context-aware AI applications using LangChain's modular approach </li><li>Develop a GenAI web application with Flask, integrating advanced features such as JSON output parsing for structured AI responses </li><li>Evaluate and compare different language models to select the most suitable for specific use cases, ensuring optimal performance and reliability </li></ul><h1>Course Outline</h1><div>This course consists of three modules.<br /><br /></div><h1><strong>Module 1: Foundations of Generative AI and Prompt Engineering</strong></h1><div><strong>Welcome to the Course</strong></div><ul><li>Video: Course Introduction</li><li>Video: Introduction to the Professional Certificate</li><li>Reading: Course Overview</li><li>Reading: Helpful Tips for Course Completion</li></ul><div><strong>[Optional] Generative AI Essentials</strong></div><ul><li>Reading: About this optional lesson</li><li>Video: Introduction to Generative AI</li><li>Video: What are Generative AI models?</li><li>Video: What is NLP (Natural Language Processing)?</li><li>Reading: Comprehensive Guide to Generative AI</li><li>Practice Quiz: Generative AI Essentials</li></ul><div><strong>Working with Prompt Engineering and Prompt Templates</strong></div><ul><li>Video: Introduction to In-Context Learning</li><li>Video: Introduction to LangChain</li><li>Video: Advanced Methods of Prompt Engineering</li><li>Video: LangChain LCEL Chaining method</li><li>Reading: (Optional) What is Prompt Engineering, and why do we care?</li><li>Lab: Master Prompt Engineering and LangChain Prompt Templates</li><li>Practice Quiz: Working with Prompt Engineering and Prompt Templates</li></ul><div><strong>Module Summary and Evaluation</strong></div><ul><li>Reading: Summary and Highlights: Foundations of Generative AI and Prompt Engineering</li><li>Reading: Cheat Sheet: Foundations of Generative AI and LangChain </li><li>Graded Quiz: Foundations of Generative AI and Prompt Engineering </li><li>[Optional] Discussion Prompt: Meet and Greet [ungraded]</li></ul><div><br /></div><h1><strong>Module 2: Introduction to LangChain in GenAI Applications</strong></h1><div><strong>LangChain Core Components and Advanced Features </strong></div><ul><li>Reading: Recap: Introduction to LangChain </li><li>Video: LangChain: Core Concepts</li><li>LangChain Chains and Agents for Building Applications</li><li>(Optional) LangChain LCEL Chaining Method</li><li>Lab: Build Smarter AI Apps: Empower LLMs with LangChain</li><li>Practice Quiz: LangChain Core Components and Advanced Features </li></ul><div><strong>Module Summary and Evaluation</strong></div><ul><li>Reading: Summary and Highlights: Introduction to LangChain in GenAI Applications </li><li>Reading: Cheat Sheet: Introduction to LangChain in GenAI applications </li><li>Graded Quiz: Introduction to LangChain in GenAI applications</li></ul><h1><strong>Module 3: Build a Generative AI Application with LangChain</strong></h1><div><strong>Application Development Workflow with Generative AI</strong></div><ul><li>Video: Choose the right AI model for your use case</li><li>Video: From Idea to AI: Building Applications with Generative AI</li><li>Video: Introduction to Flask</li><li>(Optional) Reading: Python with Flask for Large Scale Projects</li><li>Cheat Sheet (Optional): Web Development Using Flask</li><li>Lab: Hands-on with GenAI: Choosing the Right Model for Your Application</li><li>Practice Quiz: Application Development Workflow with Generative AI</li></ul><div><strong>Module Summary and Evaluation</strong></div><ul><li>Reading: Summary and Highlights: Build a Generative AI Application with LangChain </li><li>Reading: Cheat Sheet: Build GenAI Application with LangChain</li><li>Graded Quiz: Hands-on with GenAI: Choosing the Right Model for Your Application </li></ul><div><strong>Course Wrap Up</strong></div><ul><li>Video: Course Wrap-up </li><li>Reading: Congratulations and Next Steps</li><li>Reading: Team and Acknowledgments</li></ul><h1>Prerequisites</h1><div>Python programming skills and experience are required, as the course emphasizes coding and application development. Additionally, fundamental knowledge of AI and web development is highly recommended. A strong foundation in generative AI is recommended but not required.</div>
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Develop Generative AI Applications: Get Started

Get ready to power up your resume with the GenAI development skills.During this course you’ll explore core prompt engineering strategies—like in-context learning and chain-of-thought—and create and manage robust prompt templates. You will follow best practices to handle common errors and experiment with different LLMs and configurations to strengthen your outputs.You’ll dive deeper into LangChain, mastering chains, tools, and agents to create smarter, more responsive applications. Through interactive labs, you’ll build a complete generative AI app using Python.

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  <div>In this course, you will explore the impact of generative artificial intelligence (AI) on society, the workforce, organizations, and the environment.<br /><br /></div><div>This course is suitable for anyone interested in learning about the ethical, economic, and social implications of generative AI and how generative AI can be used responsibly. It will benefit professionals, executives, policymakers, and students.<br /><br /></div><div>In this course, you will learn about the ethical concerns of generative AI, including data privacy, biases, copyright infringement, and hallucination. You will identify the misuses related to generative AI, including deepfakes.<br /><br /></div><div>Further, in the course, you will examine the considerations for the responsible use of generative AI. You will explore the broader implications of generative AI on transparency, accountability, privacy, and safety. Finally, you will learn about the socioeconomic impacts of generative AI.<br /><br /></div><div>The examples and cases included in the course help to realize the considerations for generative AI in real-life scenarios. You will hear from practitioners about the realities, limitations, and ethical considerations of generative AI.<br /><br />After completing this course, you will be able to:</div><ul><li>Describe the limitations of generative AI and the related concerns.</li><li>Discuss the ethical issues, concerns, and misuses associated with generative AI.</li><li>Explain the considerations for the responsible use of generative AI.</li><li>Discuss the economic and social impact of generative AI.</li><li>Explain the impact of generative AI on jobs and the workforce.</li></ul><h1>Course Syllabus</h1><div><strong>Welcome</strong></div><ul><li>Video: Course Introduction</li><li>Reading: Course Overview</li><li>Reading: Program/Specialization Overview</li><li>Reading: Helpful Tips for Course Completion</li><li>General Information</li><li>Learning Objectives and Syllabus</li><li>Grading Scheme</li></ul><div><strong>Module 1: Limitations and Ethical Issues of Generative AI</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Limitations of Generative AI</li><li>Video: Issues and Concerns About Generative AI</li><li>Video: Hallucinations of Text and Image-Generating LLMs</li><li>Video: Hallucinations of Code-Generating LLMs</li><li>Lab: Hallucinations of LLMs</li><li>Video: AI Portraits and Deepfakes</li><li>Lab: Creating AI Portraits</li><li>Video: Enhancing LLM Accuracy with RAG</li><li>Video: Legal Issues and Implications of Generative AI</li><li>Discussion Prompt: Ethical Issues about Generative AI</li><li>Expert Viewpoints Video: Issues and Ethical Concerns Associated with Generative AI</li><li>Expert Viewpoints Video: Limitations and Challenges of Generative AI</li><li>Expert Viewpoints Video: Regulating Challenges Posed by Generative AI</li><li>Reading: Module Summary</li><li>Practice Quiz: Limitations, Concerns, and Issues of Generative AI</li><li>Graded Quiz: Limitations and Ethical Issues of Generative AI</li></ul><div><strong>Module 2: Social and Economic Impact and Responsible Generative AI</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Considerations for Responsible Generative AI</li><li>Video: Implementing Responsible Generative AI Across Domains</li><li>Lab: Ethical Considerations for Generative AI in Different Domains</li><li>Video: AI Ethics: Perspective of Key Players</li><li>Practice Quiz: Considerations for Responsible AI</li><li>Video: Economic Implications of Generative AI</li><li>Video: Social Implications of Generative AI</li><li>Video: A Reimagined Workforce with Generative AI</li><li>Discussion Prompt: Generative AI's Influence on Mental Health</li><li>Expert Viewpoints Video: AI Ethics Understanding the Focus of Key Players</li><li>Expert Viewpoints Video: What are the Key Considerations for the Responsible Use of Generative AI</li><li>Expert Viewpoints Video: Impact of Generative AI on Society</li><li>Expert Viewpoints Video: Integrating Generative AI into Organizational Culture</li><li>Reading: Module Summary</li><li>Practice Quiz: Social and Economic Impact</li><li>Graded Quiz: Social and Economic Impact and Responsible Generative AI</li></ul><div><strong>Module 3: Course Quiz and Final Project</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Glossary: Generative AI: Impact, Considerations, and Ethical Issues</li><li>Reading: Implementing Responsible Generative AI</li><li>Final Project: Preparing Your Mind for Generative AI</li><li>Final Exam: Generative AI: Impact, Considerations, and Ethical Issues</li></ul><div><strong>Course Wrap-Up</strong></div><ul><li>Reading: Congratulations and Next Steps</li><li>Thanks from the Course Team</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>This course is designed for anyone interested in the subject of generative AI. No prior knowledge or experience of programming is required.  <br /><br />**Note:** This platform works best with current versions of Chrome, Edge, Firefox or Safari.</div>
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Impact, Ethics, and Issues with Generative AI

Dive into the world of Generative AI with a focus on different ethical factors related to data privacy, security, the workforce, and the environment. Learn about the socioeconomic impacts of generative AI and related issues such as job and copyright implications. You'll also explore the ethical concerns related to generative AI and examine how to use it responsibly.

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  <h1>About this course</h1><div>Begin your cloud computing mastery with this easy-to-follow, self-paced course. Gain the essential knowledge needed to understand cloud computing from a business perspective and as a hands-on cloud practitioner.<br /><br />This course immerses you in the world of notable cloud service providers, including AWS, Google, IBM, and Microsoft. Explore their offered services and examine real-world applications through industry-specific case studies. You'll also dive into cloud adoption and its connection with technologies such as blockchain, analytics, and AI.<br /><br />Discover the diverse cloud service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS)—and deployment models—public, private, and hybrid. You'll grasp the core elements of cloud infrastructure, including VMs, networking, storage types, and CDNs. You’ll learn about emerging trends like Hybrid Multicloud, Microservices, Serverless, DevOps, Cloud Native, and Application Modernization. Learn the basics of cloud security, monitoring, and understand various roles in the cloud industry.<br /><br />Throughout the course, you’ll hear from subject matter experts who will share their insights into Cloud technology and work as a Cloud Practitioner.<br /><br />You'll gain hands-on experience, having deployed an application on IBM Cloud—a shareable project that makes for an impressive employment portfolio addition!<br /><br />Whether you're an executive, manager, student, or professional seeking familiarity with cloud computing terminology and concepts, or you aim for a solid grounding in cloud computing for a career as a cloud engineer, full stack developer, DevOps engineer, service reliability engineer, or cybersecurity analyst, this course is your starting point.<br /><br /><strong>What you'll learn<br /><br /></strong>After completing this course, a learner will be able to:</div><ul><li>Define cloud computing and explain essential characteristics, history, the business case for Cloud, and the emerging technologies enabled by Cloud.</li><li>Describe Cloud service models, including IaaS, PaaS, SaaS</li><li>Describe Public, Private, and Hybrid Cloud deployment models.</li><li>Explain Cloud infrastructure components.</li><li>Explain emerging cloud-related trends, including Hybrid, Multicloud, Microservices, Serverless, Cloud Native, DevOps, and Application Modernization.</li><li>List and describe services of popular cloud platforms, including AWS, Microsoft Azure, Google Cloud, IBM Cloud, Alibaba Cloud, and others.</li></ul><h1>Course syllabus</h1><div><strong>Module 1: Overview of Cloud Computing</strong></div><ul><li>Introduction and Learning Objectives</li><li>Definition and essential characteristics of cloud computing</li><li>Expert Viewpoints: Definition and Essential Characteristics of Cloud Computing</li><li>History and Evolution of Cloud Computing</li><li>Key Considerations for Cloud Computing</li><li>Key Cloud Service Providers and Their Services</li><li>Cloud Adoption - No Longer a Choice</li><li>Expert Viewpoints: Cloud Adoption Benefits and Use Cases</li><li>Cloud Adoption - Some Case Studies</li><li>Internet of Things on the Cloud</li><li>Artificial Intelligence on the Cloud</li><li>Blockchain and Analytics on the Cloud</li></ul><div><strong>Module 2: Cloud Computing Models</strong></div><ul><li>Introduction and Learning Objectives</li><li>Overview of Cloud Service Models</li><li>Infrastructure-as-a-Service</li><li>Platform-as-a-Service</li><li>Software-as-a-Service</li><li>Public Cloud</li><li>Private Cloud</li><li>Hybrid Cloud</li><li>Expert Viewpoints: Cloud Computing Service and Deployment Models</li><li>Community Cloud</li></ul><div><strong>Module 3: Components of Cloud Computing</strong></div><ul><li>Introduction and Learning Objectives</li><li>Overview of Cloud Infrastructure</li><li>Virtualization and Virtual Machines Explained</li><li>Types of Virtual Machines</li><li>Bare Metal Servers</li><li>Secure Cloud Networking</li><li>Containers</li><li>Expert Viewpoints: Components of Cloud Computing</li><li>Basics of Cloud Storage</li><li>File Storage</li><li>Block Storage</li><li>Object Storage Overview</li><li>Object Storage - Tiers and APIs</li><li>Content Delivery Networks</li><li>Expert Viewpoints: Cloud Storage</li></ul><div><strong>Module 4 - Emergent Trends and Practices</strong></div><ul><li>Introduction and Learning Objectives</li><li>Hybrid Multi-Cloud</li><li>Microservices</li><li>Serverless Computing</li><li>Cloud Native Applications</li><li>DevOps on the Cloud</li><li>Application Modernization</li><li>Expert Viewpoints: Cloud Native and Emergent Cloud Trends</li></ul><div><strong>Module 5: Cloud Security and Monitoring, Case Studies, and Jobs</strong></div><ul><li>Introduction and Learning Objectives</li><li>What is Cloud Security - Part 1</li><li>What is Cloud Security - Part 2</li><li>Policies and Principles of Access Management</li><li>Identity and Access Management</li><li>Cloud encryption</li><li>Cloud Monitoring Basics and Benefits</li><li>Cloud Monitoring Benefits</li><li>Case Studies in Different Industry Verticals</li><li>Career Opportunities and Job Roles in Cloud Computing</li><li>Expert Viewpoints: Job Market for Cloud Computing</li><li>Final Project: Deploy an application on the cloud</li><li>HONORS Assignment: Architect a Cloud-based solution</li><li>Final Exam</li></ul><h1>Recommended skills prior to taking the course</h1><div>Basic computer literacy. No prior knowledge of Cloud Computing or Computer Programming.</div>
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Introduction to Cloud Computing

This course introduces you to the core concepts of cloud computing. You will gain the foundational knowledge required for understanding cloud computing from both business and practitioner perspectives. You will also learn about cloud adoption and emerging technologies, cloud computing service and deployment models, different types of cloud storage, and emergent cloud trends.

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  <div>In this project, you will apply your knowledge of front-end and back-end development to build and deploy a full-stack real-world web application on the cloud.<br /><br />Your project will showcase your understanding of the user experience and user interface design process, and your skills and technologies with Django, Python, Node.js, and Containers.<br /><br />After completing this project, you will have gained hands-on practical experience with a real-world project and be able to demonstrate your proficiency in front-end and back-end skills to potential employers.</div><h1>Learning Objectives:</h1><div>By the end of this course, you will be able to:</div><ul><li>Articulate the attributes of multiple cloud services, including Watson AI, Cloudant, and Cloud Object Storage.</li><li>Sharpen your skillset using JavaScript, React.js, Python, Node.js, Express and more.</li><li>Build a real-world web application using front-end and back-end technology.</li><li>Deploy your Django full-stack web application on the cloud</li></ul><div><br /></div><h1>Prerequisites:</h1><div>Complete all previous courses within the Full-Stack Cloud Developer Professional Certificate </div><div><br /></div><h1>Course Syllabus:</h1><div><strong>Module 1: Application – Static Pages </strong></div><div><strong>Module 2: Application – User Management </strong></div><div><strong>Module 3: Back End Services </strong></div><div><strong>Module 4: Application – Dynamic Pages (React.js) </strong></div><div><strong>Module 5: CI/CD, Containerize &amp; Deploy to Kubernetes </strong></div><div><strong>Module 6: Share Your Project </strong></div>
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Full Stack Software Developer Capstone

While completing this project, you will apply your front-end and back-end development knowledge to build and deploy the application on the cloud. 

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  <div>Collaboration means so much more than simply working together; it goes beyond that, and this course teaches you how. Through collaboration, you can achieve so much more than you could if you had worked alone. Some of the essential skills taught in this course include effectively communicating with the people you work with, being a team player, and working as a team towards a shared goal.<br /><br /></div><div>In today’s day and age and in the modern workspace, group collaboration is not limited to just the workplace. Collaboration is no longer just in person, as collaboration is now done virtually all the time! This course will teach you how to collaborate both virtually and in person.<br /><br /></div><div>This short course not only teaches you about some of the drawbacks and obstacles of different styles of communication, it also teaches you how to recognize and apply proper and different methods of communication. You will learn to overcome obstacles that you may face when collaborating and strive for professional success.<br /><br /></div><div>Effective collaboration requires the involvement of diverse individuals and teamwork. When working with others, you need to be able to read their body language and understand their behaviors. In this course, you will learn how to do this and work successfully together.<br /><br /></div><div>By the end of this self-paced, short course, you will have developed the skills you need to collaborate with a team, others in your company, business partners, and clients.<br /><br /></div><div>This course is part of the People and Power Skills Professional Certificate from IBM, which consists of a series of short courses to help you develop essential soft skills for success in the workplace.<br /><br /><strong>What you'll learn</strong></div><ul><li>Identify different collaborative barriers as well as the specific behaviors that enhance or get in the way of collaboration</li><li>Go through the four stages of team development using different collaborative techniques</li><li>Improve teamwork and collaboration in your professional environment</li><li>Effectively lead and participate in virtual meetings, an increasingly popular form of collaboration</li></ul><div><strong>The course is composed of the following lessons:<br /></strong><br /></div><div>- Collaborate Effectively: An Overview</div><div>- About the Course</div><div>- What is collaboration, and why is it so important?</div><div>- How can you enhance your collaboration with colleagues?</div><div>- How can you help your team collaborate?</div><div>- What are the challenges of virtual collaboration, and how can you tackle them?</div><div>- What tools can you use for virtual collaboration?</div><div>- How can you make virtual meetings effective?</div><div>- Course-end Assessment<br /><br /></div><div><strong>Prerequisites<br /></strong><br />This course does not require any previous work experience and is great if you are just beginning your career or if you are looking for a skill refresher.<br /><br /></div>
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Soft Skills: Collaborate Effectively

Learn the fundamentals of collaborating and communicating with others in a professional environment in order to achieve professional success.

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  <div><strong>About this course</strong></div><div>When submitting work in a professional setting, it is crucial to meet both the quality and time expectations set by your employer. This short course will teach you about how to deliver quality work with consistency and efficiency.<br /><br /></div><div>Effective research skills play a vital role in ensuring the delivery of quality work. By taking this short, self-paced course, you will learn exactly how to do that. You will also learn a variety of other skills that are essential, such as a five-step process that will teach you how to create and deliver quality work.<br /><br /></div><div>The skills taught in this course are fundamental skills that are important in any job you may have, especially office or business-related jobs. The content provided in this course applies to your everyday work life and will be a stepping stone in your path to success.<br /><br /></div><div>This course is part of the People and Power Skills Professional Certificate from IBM.<br /><br /></div><div><strong>What you'll learn</strong></div><ul><li>Deliver work consistently and on time</li><li>Apply a five-step process that will help you deliver high-quality work</li><li>Create and deliver work that helps solve problems and reduces effort for the person or group requesting it</li><li>Become a trusted advisor to clients and colleagues by working with agility while applying the quality work process</li></ul><div><strong>Prerequisites<br /></strong><br /></div><div>No prior experience is necessary! This course is suitable for those taking it as a career starter or even just a skill refresher.<br /><br /></div><div><strong>Curriculum</strong></div><div><br /></div><div>The course is composed of the following lessons:<br /><br /></div><div>- Delivering Quality Work with Agility: An overview</div><div>- About the Course</div><div>- Topic 1: What do I need to know?</div><div>- Topic 2: How do I prepare?</div><div>- Topic 3: How do I do my research?</div><div>- Topic 4: How do I decide what to do?</div><div>- Topic 5: How do I do it?</div><div>- Topic 6: How do I deliver it?</div><div>- Topic 7: Who benefits when I deliver quality work?</div><div>- Course-end Assessment</div>
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Soft Skills: Deliver Quality Work with Agility

Understand the importance of being able to create and deliver high-quality work efficiently, as it is a crucial soft skill for enhancing professional success.

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  <div><strong>About this course</strong></div><div>The most essential skills needed to be successful in your professional life are being able to effectively communicate and interact with the people you work with. These are called interpersonal skills. Being able to talk with your co-workers in a way that establishes respect and eminence is an incredibly important ability to have in the workplace.<br /><br /></div><div>This short, self-paced course will teach you the skills you need in order to communicate and interact with people in a way that shows confidence and gives them a sense of trust. In this course, you will learn skills such as asserting your influence, different communication styles, listening skills, and more!<br /><br /></div><div>No matter where you work, conflicts are something that will naturally arise, and after taking this course, you will be able to recognize and apply the interpersonal skills you need in order to resolve them. The skills offered in this course are foundational soft skills to have and will take you one step closer to professional success.<br /><br /></div><div>This short course can be taken by anyone who wants to learn, no matter how much experience they have. Whether you are taking this course as a career starter or skill refresher, this course is for everyone!<br /><br /></div><div>This course is part of the People and Power Skills Professional Certificate from IBM, which consists of a series of short courses to help you develop essential soft skills for success in the workplace.<br /><br /></div><div><strong>What you'll learn</strong></div><ul><li>Analyze different communication styles as well as their strengths and weaknesses, and when they are appropriate to use</li><li>Build and maintain trust with your co-workers and increase your influence and eminence in the workplace</li><li>Identify ways to approach and mediate workplace conflicts</li><li>Demonstrate active listening skills to enhance your understanding of workplace issues</li></ul><div><strong>Prerequisites<br /></strong><br /></div><div>This course is suitable for anyone, regardless of previous experience. This course is also perfect for people just starting or in their early careers.<br /><br /></div><div><strong>Curriculum</strong></div><div><br /></div><div>The course is composed of the following lessons:</div><div>- Interpersonal skills: An overview</div><div>- About the course</div><div>- Topic 1: What is my communication style?</div><div>- Topic 2: How can I become a better communicator?</div><div>- Topic 3: How can I behave assertively?</div><div>- Topic 4: How can I increase my influence?</div><div>- Topic 5: How should I approach workplace conflict?</div><div>- Topic 6: How can I resolve workplace conflict?</div><div>- Course-end Assessment</div>
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Soft Skills: Develop Interpersonal Skills

Learn key interpersonal skills: how to effectively communicate and interact with others while establishing your presence in a professional workspace!

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  <div><strong>About this course</strong></div><div>This short course is the final assessment for the People and Power Skills Professional Certificate. It serves as a culmination of the knowledge and abilities gained throughout the entire program. By completing this assessment, you will demonstrate your proficiency in key areas essential for professional success.<br /><br /></div><div>The People and Power Skills Professional Certificate is a comprehensive program designed to equip you with the essential soft skills necessary to excel in today's professional landscape. This certificate program focuses on developing crucial soft skills that are highly sought after by employers across industries.<br /><br /></div><div>Before taking this assessment, please ensure that you have completed the previous 5 courses offered in the <a href="https://www.edx.org/professional-certificate/ibm-people-and-power-skills">People and Power Skills Professional Certificate</a>. These include:</div><ol><li><a href="https://www.edx.org/course/soft-skills-present-with-purpose">Soft Skills: Present with Purpose</a></li><li><a href="https://www.edx.org/course/soft-skills-solve-problems-w-creative-critical-thinking">Soft Skills: Solve Problems w/ Creative &amp; Critical Thinking</a></li><li><a href="https://www.edx.org/course/soft-skills-develop-interpersonal-skills">Soft Skills: Develop Interpersonal Skills</a></li><li><a href="https://www.edx.org/course/soft-skills-deliver-quality-work-with-agility">Soft Skills: Deliver Quality Work with Agility</a></li><li><a href="https://www.edx.org/course/people-skills-collaborate-effectively">Soft Skills: Collaborate Effectively</a></li></ol><div>In this assessment, you will be presented with many real-life inspired scenarios and be questioned on what to do if you were to encounter them. You will be taking your knowledge of previous courses in this certificate and applying them to these scenarios.<br /><br /></div><div>Upon completion of this course, you will receive your Professional Certificate in People and Power Skills if you are in the verified track for the entire program.<br /><br /></div><div><strong>What you'll learn</strong></div><ul><li>Analyze and solve problems with the use of creative and critical thinking</li><li>Show a working knowledge of interpersonal skills by identifying different communication styles and conflict responses</li><li>Exhibit your skills in creating and delivering presentations that leave a lasting impression</li><li>Showcase your ability to create and deliver quality work in a professional environment</li><li>Apply your knowledge of techniques to collaborate effectively</li></ul><div><strong>Prerequisites<br /></strong><br /></div><div>Before taking this course, please ensure you have completed all of the other 5 courses in the IBM People and Power Skills Professional Certificate.<br /><br /></div><div><strong>Curriculum</strong></div><div><br /></div><div>The course is composed of the following lessons:<br /><br /></div><div>- People and Power Skills Assessment: An Overview</div><div>- About the Course</div><div>- Check your Knowledge</div><div>- Continue your Learning</div>
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Soft Skills: People and Power Skills Assessment

This course contains the final assessment where you will apply your knowledge of the courses in the People and Power Skills Professional Certificate!

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  <div><strong>About this course</strong></div><div>Being able to create a presentation is an important skill in a professional work environment, especially when you are working in an office or business-related setting. Knowing how to create a presentation that leaves a lasting impact is an essential skill to have.<br /><br /></div><div>This short course was created to equip you with the skills to do exactly that. In this course, you will learn to create and deliver a presentation that keeps your audience well-informed, engaged, and leaves them impressed and with a lasting impression. Delivering a good presentation is not only about reading memorized lines off a slide; it is also a matter of confidence, body language, managing nerves, and being prepared for any questions that may be thrown your way by your audience.<br /><br /></div><div>By the end of this short course, you will know how to create and deliver an effective presentation with poise and confidence, which will contribute to your workplace presence and help you achieve professional success.<br /><br /></div><div>This course is part of the People and Power Skills Professional Certificate from IBM, which consists of a series of short courses to help you develop essential soft skills for success in the workplace.<br /><br /></div><div><strong>What you'll learn</strong></div><ul><li>Present and deliver presentations with confidence</li><li>Create powerful and engaging presentations that keep your audience's attention</li><li>Use storytelling, props, and discussion techniques to enhance your presentation</li><li>Learn how to keep calm and be able to deal with any unexpected problems that may arise during your presentation</li></ul><div><strong>Prerequisites<br /></strong><br /></div><div>No prior work experience required! This is a great course to take as both a career starter or a skill refresher.<br /><br /></div><div><strong>Curriculum</strong></div><div><br /></div><div>The course is composed of the following lessons:</div><div>- Present with Purpose: An overview</div><div>- About the Course</div><div>- Present with Purpose: An Introduction</div><div>- Topic 1: How do I focus on my objectives?</div><div>- Topic 2: How do I identify my audience?</div><div>- Topic 3: How do I build my structure?</div><div>- Topic 4: How do I design my deck?</div><div>- Topic 5: How do I present more effectively?</div><div>- Topic 6: How do I manage my nerves?</div><div>- Topic 7: How do I deal with the unexpected?</div><div>- Course-end Assessment</div>
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Soft Skills: Present with Purpose

This short course will teach you how to create and deliver presentations that leave an effective and lasting impact on your audience!

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  <div>In this course, you will discover the transformative impact of generative AI on businesses and professionals and how generative is elevating opportunities for businesses and professionals in different industries.<br /><br />This course is designed for anyone interested in learning about business and career opportunities through generative AI. It will benefit a diverse audience, including professionals in various domains, executives, managers, startup founders, and students.<br /><br />In this course, you will discover the influence of generative AI on existing businesses and opportunities for new businesses. You will learn how to make a business ready for generative AI adoption. You will identify the impact of generative AI across various industries.<br /><br />Next, you will discover the potential career opportunities in the generative AI sector. You will learn how generative AI can impact and enhance the existing functions, skills, and job roles in different sectors.<br /><br />In this course, you will hear from practitioners about the current trends and future perspectives of generative AI, exploring its potential to reshape industries and redefine professions. The course includes labs and projects, providing you with an opportunity to demonstrate your skills and understanding of generative AI.</div><div><br /></div><h1>Course Syllabus</h1><div><strong> Generative AI in Business: Trends, Ideas, and Implementation</strong></div><ul><li>Current Trends and Future Perspectives of Generative AI</li><li>Elevating Businesses through Generative AI</li><li>An Ecosystem of Generative AI Providers </li><li>RAG: Opportunity and Potential Applications for Business</li><li>Impact of Generative AI in Different Industries</li></ul><div><strong>Generative AI: Impact and Opportunities for Career Growth</strong></div><ul><li>Career Opportunities in Generative AI</li><li>Enhancing Your Career with Generative AI</li><li>Generative AI for Content Creators </li><li>Generative AI Applications for Content Creators</li><li>Generative AI for IT Professionals</li><li>Generative AI Applications for IT Professionals</li><li>Custom GPTs: Personalized AI</li><li>Creating Custom GPTs</li><li>Generative AI for Executives and Managers</li></ul><div><strong>Course Quiz, Project, and Wrap-up<br /></strong><br /></div><h1><strong>What you'll learn</strong></h1><ul><li>Explain the transformative impact of generative AI on the business and industry landscape.</li><li>Identify key indicators of readiness for integrating generative AI into business.</li><li>Explore potential career opportunities in generative AI.</li><li>Analyze how generative AI can enhance existing careers in diverse fields.</li><li>Apply generative AI to boost your productivity at work.</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>This course is designed for anyone interested in the subject of generative AI. No prior knowledge or experience of programming is required.  <br /><br />**Note:** This platform works best with current versions of Chrome, Edge, Firefox or Safari.</div>
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Elevating Businesses and Careers with Generative AI

Unlock the power of generative AI for your career and business success! Dive into this comprehensive course designed for professionals and enthusiasts eager to explore the dynamic world of generative AI. Learn how to leverage generative AI for existing businesses, identify new opportunities, and adapt your skills for tomorrow's job market. Gain insights from industry experts, hands-on experience, and emerge ready to thrive in the AI-driven future. Enroll now to stay ahead in the ever-evolving landscape of technology and innovation.

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  <div>In this Capstone you’ll demonstrate your ability to perform like a Data Engineer. Your mission is to design, implement, and manage a complete data and analytics platform consisting of relational and non-relational databases, data warehouses, data pipelines, big data processing engines, and Business Intelligence (BI) tools.<br /><br /></div><div>This Capstone project will require that you apply and sharpen the skills and knowledge you developed in the various courses in the IBM Data Engineering Professional Certificate and utilize multiple tools and technologies to design databases, collect data from multiple sources, extract, transform and load data into a data warehouse, and utilize a cloud-based BI tool to create analytic reports and visualizations. You will also implement predictive analytics and machine learning models using big data tools and techniques.<br /><br /></div><div>This capstone requires significant amount of hands-on lab effort throughout the course. You’ll exhibit your knowledge and proficiency working with Python, Bash scripts, SQL, NoSQL, RDBMSes, ETL, MySQL, PostgreSQL, Db2, MongoDB, Apache Airflow, Apache Spark, and Cognos Analytics.<br /><br /></div><div>Upon successfully completing this Capstone, you should have the confidence and portfolio to take on real-world data engineering projects and showcase your abilities to perform as an entry-level data engineer.</div><div><br /></div><h1>What you will learn: </h1><div>After completing this course, you will be able to: </div><ul><li>Build a complete data and analytics platform.</li><li>Setup, manage, and query relational and NoSQL databases.</li><li>Create data pipelines and ETL processes using Apache Airflow.</li><li>Design and populate a star/snowflake schema data warehouse and query it using SQL.</li><li>Analyze warehouse data using the Business Intelligence (BI) tool Cognos Analytics to create reports and dashboards.</li><li>Deploy a big data machine learning model using Apache Spark</li></ul><h1>Course Syllabus</h1><div><strong>Module 1 - Data Platform Architecture and OLTP Database</strong></div><ul><li>Assignment Overview</li><li>OLTP Database</li><li>OLTP Database Requirements and Design</li><li>Hands-on Lab: OLTP Database</li><li>Checklist: OLTP Database</li><li>Graded Quiz: OLTP Database</li></ul><div><strong>Module 2 - Querying Data in NoSQL Databases</strong></div><ul><li>Module Introduction and Learning Objectives</li><li>Assignment Overview</li><li>Querying data in NoSQL databases</li><li>Hands-on Lab: Querying data in NoSQL databases</li><li>Checklist: Querying data in NoSQL databases</li><li>Graded Quiz: Querying data in NoSQL databases</li></ul><div><strong>Module 3 - Build a Data Warehouse</strong></div><ul><li>Module Introduction and Learning Objectives</li><li>Assignment Overview</li><li>Hands-on Lab: Data Warehousing</li><li>Checklist: Data Warehousing</li><li>Hands-on Lab: Data Warehousing Reporting</li><li>Checklist: Data Warehousing Reporting</li><li>Graded Quiz: Data Warehousing &amp; Reporting</li></ul><div><strong>Module 4 - Data Analytics</strong></div><ul><li>Module Introduction and Learning Objectives</li><li>Assignment Overview</li><li>Hands-on Lab: Getting Started with Cognos Dashboard Embedded (Optional)</li><li>Dashboard Creation</li><li>Hands-on Lab: Dashboard Creation</li><li>Checklist: Dashboard Creation</li><li>Graded Quiz: Dashboard Creation</li></ul><div><strong>Module 5 - ETL &amp; Data Pipelines</strong></div><ul><li>Module Introduction and Learning Objectives</li><li>Assignment Overview</li><li>ETL &amp; Data Pipelines using Apache Airflow</li><li>Hands-on Lab: ETL</li><li>Checklist: ETL</li><li>Hands-on Lab: Data Pipelines using Apache Airflow</li><li>Checklist: Data Pipelines using Apache Airflow</li><li>Graded Quiz: ETL &amp; Data Pipelines using Apache Airflow</li></ul><div><strong>Module 6 - Big Data Analytics with Spark</strong></div><ul><li>Module Introduction and Learning Objectives</li><li>Assignment Overview</li><li>Big Data Analytics with Spark</li><li>Practice Hands-on Lab: Saving and loading a SparkML model</li><li>Hands-on Lab: SparkML Ops</li><li>Checklist: Big Data Analytics with Spark</li><li>Graded Quiz: Big Data Analytics with Spark</li></ul><div><strong>Module 7 - Final Submission</strong></div><ul><li>Final Project</li><li>Peer Review: Submit your Work and Review your Peers</li><li>Wrap Up</li><li>Reading: Congrats &amp; Next Steps</li><li>Reading: Team &amp; Acknowledgements</li></ul><h1>General Information</h1><ul><li>This course is self-paced. </li><li>This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari. </li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>In order to be successful in this course you should have a working knowledge of: </div><ul><li>Relational and NoSQL databases </li><li>SQL, Python, and Shell scripting </li><li>ETL with Airflow and Kafka </li><li>Data Warehousing, Cubes, Rollups, and Materialized views/MQTs </li><li>BI tools such as Cognos Analytics </li><li>Big Data analytics with Apache Spark </li></ul><div>It is highly recommended that you complete all the preceding courses in the IBM Data Engineering Professional Certificate. </div>
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Data Engineering Capstone Project

This Capstone Project is designed for you to apply and showcase your skills and knowledge in Data Engineering, including SQL, NoSQL, RDBMS, Bash, Python, ETL, Data Warehousing, BI tools, and Big Data. 

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  <div>Databases are the backbone of modern applications, powering everything from large scale enterprise systems to web applications.  <br /><br />This course gives you the comprehensive grounding you need to work with databases using Java programming. Whether you have a little or no knowledge of databases, if you’re keen to understand the different types of databases and how to work with these databases using Java, this course is for you!   <br /><br />During the course, you’ll explore the fundamentals of databases and Java Database Connectivity (JDBC). You’ll get hands-on developing database applications using Spring Boot. Plus, you’ll work with Hibernate and explore other databases such as NoSQL, SQL Graph and time series databases.  <br /><br />Throughout the course, you’ll complete hands-on labs and gain valuable practical experience applying your skills. Plus, you’ll complete a final project where you apply your knowledge to a real-world scenario; great for chatting about in interviews!  <br /><br />If you’re looking to build the job-ready skills you need to develop Java applications with databases, enroll today.<br /><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Fundamentals of Databases and JDBC</strong><br /><br />This module introduces the foundational concepts of relational databases and their integration with Java using JDBC. It covers database design basics, setting up connections, and performing CRUD operations programmatically.<br /><br /><strong>Module 2: Spring Boot for Database Applications</strong><br /><br />This module explores the use of Spring Boot to simplify database-driven application development. It covers configuring Spring Boot with databases, using Spring Data JPA for CRUD operations, and exposing database functionality through RESTful APIs. The module encourages active participation through practical exercises.<br /><br /><strong>Module 3: Hibernate and Other Databases</strong><br /><br />This module provides an in-depth understanding of Hibernate as an ORM framework. It also explains the role in handling complex database interactions. Learners will explore advanced entity relationships, caching, and query optimization. It also walks you through other modern data storage solutions such as NoSQL databases, Graph databases, and time series databases.<br /><br /><strong>Module 4: Final Project and Course Wrap-up</strong><br /><br />This module provides an opportunity for learners to develop the backend for a retail management system to be exclusively used by the admin users. You’ll be using Java, Spring Boot, and Hibernate. The system will use MySQL for structured data and a NoSQL database for unstructured data. <br /><br /></div><h1>Course Objectives</h1><ul><li>Understand databases and their role in applications</li><li>Handle basic CRUD operations with JDBC</li><li>Create connection pools and optimize them using Java</li><li>Apply abstraction using Spring Boot applications to simplify database integration</li><li>Learn to expose the database CRUD operations through RESTful APIs</li><li>Understand Java Persistence API (JPA)</li><li>Configure Hibernate in Spring Boot</li><li>Handle Advanced Entity Relationships with ORM using Hibernate</li><li>Understand the differences between the HQL and SQL query languages</li><li>Use NoSQL databases for CRUD operations<br />Configure NoSQL databases in Spring Boot</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>To get the most out of this course, you should be comfortable with the following topics and technologies:</div><ul><li>Java programming</li><li>Spring Boot</li></ul><div><br />This course requires knowledge of software engineering and Java development fundamentals, experience with using the Git and GitHub environments, and a good working knowledge of the Spring framework.</div>
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Java Development with Databases 

This course gives you the comprehensive grounding you need to work with databases using Java programming. Whether you have a little or no knowledge of databases, if you’re keen to understand the different types of databases and how to work with these databases using Java, this course is for you!   

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  <div>This course is meant for professionals with a background in data engineering, database administration, system architecture, and data analysis. <br /><br /></div><ul><li>Gain hands-on experience working with data architecture that you can showcase in your portfolio and talk about in interviews.  </li><li>Analyze and assess existing data architecture in alignment with business objectives. </li><li>Implement data migration and integration solutions, including building data pipelines. </li><li>Apply data governance and security protocols, ensuring compliance and data protection.  </li></ul><div><br /></div><div><br /></div>
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Data Architect Capstone Project

Gain practical, real-world experience in data architecture through this hands-on capstone project course, developing skills highly valued by employers. This is an ideal opportunity to demonstrate to recruiters that you have the skills and knowledge they’re looking for.  During this course, you’ll apply all that you’ve learned throughout the Data Architect Professional Certificate.As you work through the course, you’ll evaluate, design, migrate, and integrate enterprise data systems through a case study.

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  <div><strong>Course Description:</strong> <br /><br /></div><div>Generative AI (gen AI) is transforming digital marketing by enhancing efficiency, personalization, and content creation. According to a McKinsey report, AI-driven advancements could boost marketing productivity by 5–15% of total spending, adding approximately $463 billion annually. <br /><br /></div><div>Digital marketers who can leverage gen AI are in high demand, and this course gives you sought-after gen AI skills businesses need. <br /><br /></div><div>In this course, you’ll explore how gen AI automates content creation, enhances ad copy, and personalizes email campaigns and social media posts. You’ll learn gen AI-driven techniques for audience segmentation, keyword research, SEO optimization, and digital advertising to create targeted, data-driven campaigns. The course also covers AI’s role in e-commerce and email marketing, emphasizing automation, personalization, and improved campaign performance. <br /><br /></div><div>In addition, you’ll examine ethical considerations, challenges, and best practices for AI integration in digital marketing.  <br /><br /></div><div>Boost your marketing career with in-demand gen AI skills. Enroll today to enhance your resume and stand out to employers.  <br /><br /></div><div> <br /><br /></div><div><strong>Course objectives:</strong> <br /><br /></div><div>Upon successful completion of this course, learners will be able to: <br /><br /></div><ol><li><strong>Understand the fundamentals of generative AI:</strong> Gain a clear understanding of the core concepts and technologies behind generative AI and its potential applications in digital marketing. </li><li><strong>Leverage AI for content creation:</strong> Learn how to use AI tools to generate high-quality content, including articles, social media posts, product descriptions, and email copy, efficiently and effectively. </li><li><strong>Optimize digital advertising with AI:</strong> Explore how to use AI for audience segmentation, ad creative optimization, and personalized advertising campaigns across various platforms. </li><li><strong>Enhance SEO with AI:</strong> Discover how AI can be used for keyword research, content optimization, technical SEO audits, and competitor analysis to improve search engine rankings. </li><li><strong>Improve e-commerce experiences with AI:</strong> Learn how to use AI for personalized product recommendations, customer service chatbots, and targeted marketing campaigns to enhance the customer journey. </li><li><strong>Master AI-powered email marketing:</strong> Explore how to use AI to generate engaging email content, personalize email campaigns, and optimize email marketing strategies for better results. </li></ol><div> <br /><br /></div><div><strong>Course learning objectives for Coursera</strong> <br /><br /></div><ul><li>Job-ready, practical skills for leveraging generative AI in digital marketing </li><li>Generative AI tools and techniques for creating marketing content and campaigns </li><li>AI-driven strategies for improving SEO, digital advertising, and e-commerce experiences </li><li>Generative AI techniques to create engaging and personalized email content and targeted marketing strategies </li></ul><div><br /> <br /><br /></div>
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Generative AI: Accelerate your Digital Marketing Career

In this course, you’ll explore how gen AI automates content creation, enhances ad copy, and personalizes email campaigns and social media posts. You’ll learn gen AI-driven techniques for audience segmentation, keyword research, SEO optimization, and digital advertising to create targeted, data-driven campaigns. The course also covers AI’s role in e-commerce and email marketing, emphasizing automation, personalization, and improved campaign performance. In addition, you’ll examine ethical considerations, challenges, and best practices for AI integration in digital marketing.  

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  <div><strong>About this course</strong></div><div>This short, self-paced course was created to teach you how to effectively solve and analyze problems with critical and creative thinking. This course will equip you with invaluable skills that you will have to use in your day-to-day work, especially in office or business-related jobs.<br /><br /></div><div>Critical and creative thinking are important because when you encounter a problem, you need to be able to think of different ways to solve the problem, as well as have the ability to recognize and choose the best solution possible. There are certain steps you must take before finding a solution; the most important being analyzing the problem. By taking this course, you will learn a specifically designed five-step method that will help you find the root cause of a problem. By learning the process you must go through to find the problem, you will also get one step closer to finding a solution.<br /><br /></div><div>This short course is suitable to be taken by everyone – students, career starters, even experienced professionals and managers who want a skill refresher. By taking this course, you will gain the fundamental skills needed in order to successfully solve any problem and the confidence to achieve professional success.<br /><br /></div><div>This course is part of the People and Power Skills Professional Certificate from IBM, which consists of a series of short courses to help you develop essential soft skills for success in the workplace.<br /><br /></div><div><strong>What you'll learn</strong></div><ul><li>Apply critical and creative thinking to solve problems</li><li>Utilize the 5-step process in order to find the root cause of a problem</li><li>Analyze a problem and identify all possible solutions</li><li>Identify the best solution to implement when solving a problem in the workplace</li></ul><div><strong>Prerequisites<br /></strong><br /></div><div>No previous experience required! This course can be taken by anyone regardless of professional experience.<br /><br /></div><div><strong>Curriculum</strong></div><div><br /></div><div>The course is composed of the following lessons:</div><div>- Solve Problems with Creative and Critical Thinking: An Overview</div><div>- About the course</div><div>- Topic 1: What’s the problem?</div><div>- Topic 2: What’s really going on?</div><div>- Topic 3: What are my options?</div><div>- Topic 4: What is the best solution?</div><div>- Topic 5: What will success look like?</div><div>- Course-end Assessment</div>
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Solving Problems with Creative and Critical Thinking

Use critical and creative thinking to analyze and solve any problem you might encounter in the workplace, an extremely valuable skill to have in any profession!

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  <div>In this course, you will focus on Node.js and Express. Specifically, you will</div><ul><li>develop applications using asynchronous callbacks and promises</li><li>create REST APIs and perform CRUD operations</li><li>implement authentication and session management</li></ul><div>Throughout the course, you will complete numerous hands-on labs to gain practical experience. At the end of the course, you will demonstrate your Node skills with a final project to build your portfolio.<br /><br /></div><div>This course will help you succeed as a back-end or full-stack developer. It suits those in IT looking to step up in their careers or new graduates seeking to establish their server-side skills. This course suits those who need to manage cloud-centric projects.<br /><br /></div><div>Note: This course requires knowledge of JavaScript and Git.</div><div><br />After completing this course, you will be able to: </div><ul><li>Create server-side applications using the Node.js JavaScript runtime.</li><li>Extend your Node.js applications with third-party packages, including Express.</li><li>Use npm to manage Node.js packages in your Node.js application.</li><li>Write asynchronous callback functions and promises to complete asynchronous operations.</li></ul><h1>Course Syllabus</h1><div>Module 1: Introduction to Databases and Working with Node</div><ul><li>Lesson 1: Introduction to Databases  </li><li>Lesson 2: Module Wrap-up and Quiz</li></ul><div>Module 2: Working with Node and Databases</div><ul><li>Lesson 1: Introduction to working with NoSQL Databases and Node</li><li>Lesson 2: Module Wrap-up and Quiz</li></ul><div>Module 3: Working with REST APIs and advanced Node concepts</div><ul><li>Lesson 1: Restful APIs</li></ul><div>Module 4: Advanced development concepts with Node</div><ul><li>Lesson 1: Error Handling and Middleware </li><li>Lesson 2: Wrap-up and Quiz</li></ul><div>Module 5: Final Project</div><ul><li>Lesson 1: Final Project</li></ul><h1>General Information</h1><div>This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.<br /><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>The following skills are required to be successful with this course: </div><ul><li>Working knowledge of JavaScript</li><li>Working knowledge of Node and Express</li></ul><div><br /><br /></div>
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Back-end Application Development with Node.js and Express

In a recent Stack Overflow survey, Node.js was used by about 50% of the developers who answered the survey, making it the most used server-side technology. Express ranked as the fourth most popular web technology overall, making it the most popular server-side web framework.

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  <div>Interested in learning the complete process of developing cloud-native applications, from start to finish? Then this course is for you!<br /><br /></div><div>This course covers essential cloud concepts like Cloud Native Applications and Cloud Native Computing Foundations (CNCF) and their impact on cloud app developers. You'll also dive into specific tools and techniques for building these apps.<br /><br /></div><div>You’ll then move on to improving your organization’s culture through DevOps. This involves maintaining consistent behavior and high code quality through approaches like test-driven and behavior-driven development. It will help you establish uniform practices and uphold exemplary code quality.<br /><br /></div><div>Additionally, the course explains the benefits of implementing Continuous Integration (CI) and Continuous Delivery (CD) alongside Agile and Scrum methodologies. You'll also understand how aligning teams and promoting autonomy contributes to building superior systems.<br /><br /></div><div>The course also covers MongoDB principles in depth and explores IBM Cloudant, including its architecture, technologies, advantages, and common use cases.<br /><br /></div><div>Finally, the course concludes with a hands-on project. In this project, you'll deploy and modernize an application, refine user stories, add new features, and redeploy using CI/CD. This project will serve as a valuable addition to your portfolio, showcasing your newly acquired skills.<br /><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Introduction to Cloud Native</strong></div><ul><li>Welcome to Developing Cloud Native Applications</li><li>Cloud Computing Overview</li><li>Cloud Native Applications</li><li>CNCF</li><li>Hybrid Cloud (Optional)</li><li>Modernizing with Cloud Native Technologies</li></ul><div><strong>Module 2: DevOps &amp; CI/CD</strong></div><ul><li>Introduction to DevOps &amp; CI/CD</li><li>Definition of DevOps</li><li>Essential Characteristics of DevOps</li><li>Test Driven Development</li><li>Behavior Driven Development (BDD)</li><li>What Is CI/CD?</li><li>Benefits of CI/CD</li><li>Tools for DevOps, CI and CD</li><li>DevOps Tools Categories and Their Available Tools</li><li>Hands-on Lab: CI/CD in Action</li><li>Everyone is Responsible for Success</li></ul><div><strong>Module 3: Agile and Scrum</strong></div><ul><li>Introduction to Agile Development and Scrum</li><li>Agile Principles</li><li>Scrum Overview</li><li>Organizational impact of Agile</li><li>Mistaking Iterative Development for Agile</li><li>Destination Unknown</li><li>Agile Roles and the Need for Training</li><li>Creating Good User Stories</li><li>Effectively using Story Points</li><li>Building the Product Backlog</li><li>Sprint Planning</li><li>The Sprint Review</li><li>The Sprint Retrospective</li><li>Hands-on Lab: Get Set Up in ZenHub</li><li>Hands-on Lab: Creating stories in ZenHub</li></ul><div><strong>Module 4: NoSQL Databases in Cloud</strong></div><ul><li>Overview of NoSQL</li><li>Overview of MongoDB</li><li>Advantages of MongoDB</li><li>Use Cases for MongoDB</li><li>MongoDB in the Cloud IDE</li><li>Hands-on Lab: Getting Started with MongoDB</li><li>Hands-on Lab: MongoDB CRUD</li><li>CRUD Operations</li><li>Hands-On Lab: Accessing MongoDB from Python (Optional)</li></ul><div><strong>Final Project</strong></div><ul><li>Final Project Overview</li><li>Final Project Instruction</li><li>Peer Graded Assignment</li></ul><h1><strong>What you'll learn</strong></h1><div>After completing this course, a learner will be able to:</div><ul><li>Explore cloud-native applications concepts and methodologies.</li><li>Recognize CNCF’s impact, and analyze the benefits of CI/CD, Agile, and Scrum.</li><li>Recognize the DevOps culture and its significance.</li><li>Differentiate between TDD and BDD and explore the principles and characteristics of MongoDB.</li><li>Implement CI/CD practices and connect and integrate user stories to facilitate the Agile development process.</li><li>Enhance application functionality using tools and techniques.</li><li>Perform basic data operations using MongoBD and CRUD operations</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><ul><li>Familiarity with Cloud concepts and terminology </li><li>Basic literacy in Cloud Application Development </li><li>Basic knowledge of HTML and Javascript </li></ul>
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Get Started with Cloud Native, DevOps, Agile, and NoSQL

Learn to develop cloud-native applications from scratch in this comprehensive course. Covering key cloud concepts, tools, and techniques, you'll also explore DevOps culture, CI/CD practices, and MongoDB principles.

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  <div>The emergence of cloud computing has brought about a lot of changes to modern software development. Rather than large annual releases on physical mediums like CDs, modern software is increasingly released on the cloud, provided cost reduction, decreased time to market, and increased agility. These changes allow organizations to keep pace with their competitors and bring new innovations to market in ways that previously would have been unthinkable.<br /><br /></div><div>Rather than building large applications, known as monoliths, that perform all the functionality, microservices break down larger applications into smaller pieces that are independently maintainable and scalable, providing a host of benefits. This architecture is used at the largest software organizations in the world, because it provides cost benefits, team autonomy, and so many other advantages.<br /><br /></div><div>By the end of this course, you will</div><ul><li>Have a solid foundation for microservices and serverless</li><li>Deploy microservices on the cloud</li><li>Integrate microservices with serverless compute</li></ul><div>This course will introduce you to 12-factor apps and microservices, concepts that emerged to help organizations work better and faster in a cloud-native manner. You’ll then learn about serverless computing—how it works, what value it brings, and what are specific serverless technologies. You’ll get hands-on with IBM Cloud Functions, a serverless platform on IBM Cloud that lets you develop serverless apps with ease. Finally, you will learn to build and deploy applications using container images on the code engine.</div><div>The course contains several hands-on labs which allow you to apply the content you learn.</div><div><br /></div><div><strong>What you'll learn?</strong></div><ul><li>Identify the twelve factors and describe how they map to the software delivery lifecycle</li><li>Create and test Swagger documentation for REST API endpoints</li><li>Create and test a serverless function</li><li>Build and deploy applications using container images on the code engine</li></ul><div><strong>Prerequisites<br /></strong><br /></div><div>The prerequisites for this course include basic computer and cloud literacy as well as an understanding of core cloud concepts. In addition, understanding of the command line and how to use shell commands will greatly benefit you during this course.<br /><br /></div><div><strong>Curriculum</strong></div><div><br /></div><div><strong>Welcome</strong></div><ul><li>Reading: Welcome to Microservices and Serverless</li><li>Reading: General Information</li><li>Reading: Learning Objectives and Syllabus</li><li>Reading: Grading Scheme</li><li>Video: Course Introduction</li></ul><div><strong>Module 1: Introduction to MicroServices</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Twelve-Factor App Methodology</li><li>Video: What are Microservices?</li><li>Video: Comparison of Monolith vs SOA vs Microservices</li><li>Video: Microservices Patterns</li><li>Reading: Microservices Anti-Patterns</li><li>Hands-on Activity: Modernize JPetStore with Microservices</li><li>Reading: Summary and Highlights</li><li>Practice Quiz: Introduction to Microservices</li><li>Graded Quiz: Introduction to Microservices</li><li>Reading: Module 1 Glossary - Introduction to Microservices</li></ul><div><strong>Module 2: Web API Essentials: REST API and GraphQL</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: What is REST</li><li>Video: Introduction to API Gateway</li><li>Video: Creating REST APIs</li><li>Hands-on Lab: Creating a HELLO WORLD REST API with Python &amp; Flask</li><li>Video: Making API Requests using cURL and Postman</li><li>Hands-on Lab: CRUD Operations with Python</li><li>Video: Documenting and Testing REST API Swagger</li><li>Hands-on Lab: Documenting and Testing REST API Swagger</li><li>Hands-on Lab: Optional - Querying with GraphQL</li><li>Reading: Summary and Highlights</li><li>Reading: Module 2 Glossary - Web API Essentials REST</li><li>Practice Quiz: Web API Essentials - REST API and GraphQL</li><li>Graded Quiz: Web API Essentials - REST API and GraphQL (10 Questions)</li></ul><div><strong>Module 3: Serverless Overview</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: Introduction to Serverless Computing</li><li>Video: Serverless Pros and Cons</li><li>Video: Introduction to the FaaS Model</li><li>Video: The Serverless Framework</li><li>Video: Serverless Reference Architecture and Use Cases</li><li>Video: Popular Serverless Platforms</li><li>Reading: AWS Lambda</li><li>Hands-on Lab: Optional - Signing up for an AWS Account</li><li>Hands-on Lab: Optional - Creating an AWS Lambda</li><li>Reading: Summary and Highlights</li><li>Reading: Module 3 Glossary - Serverless Overview</li><li>Practice Quiz: Serverless Overview</li><li>Graded Quiz: Serverless Overview (10 Questions)</li></ul><div><strong>Module 4: Create and Deploy Microservices using Serverless</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Video: IBM Cloud Code Engine</li><li>Video: Project, Application, Build, and Jobs</li><li>Hands-on Lab: Deploying your first application on Code Engine</li><li>Video: Building Container Images for Microservices</li><li>Video: Deploying and Running Applications</li><li>Hands-on Lab: Deploying your first Docker image on Code Engine</li><li>Video: Updating Deployed Applications</li><li>Hands-on Lab: Deploy, Update, and Scale Microservices using Serverless</li><li>Reading: Summary and Highlights</li><li>Graded Quiz: Create and Deploy Microservices (10 Questions)</li><li>Reading: Module 4 Glossary - Create and Deploy Microservices</li><li>Practice Quiz: Create and Deploy Microservices</li></ul><div><strong>Final Assignment:</strong></div><ul><li>Final Project Overview and Grading Criteria</li><li>Final Project: Serverless Web Application and API</li><li>Peer-Graded Final Assignment: Serverless Web Application and API</li></ul><div><strong>Module 5: [Optional] OpenShift Essentials/Working with OpenShift and Istio</strong></div><ul><li>Reading: Module Introduction</li><li>Video: OpenShift Recap</li><li>Video: Service Mesh and Istio</li><li>Video: Microservices with OpenShift</li><li>Video: Red Hat Marketplace</li><li>Hands-on Lab: OpenShift</li><li>Reading: Summary and Highlights</li><li>Practice Quiz</li><li>Practice Quiz: OpenShift Essentials/Working with OpenShift and Istio</li></ul>
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Microservices and Serverless for Application Developers

Design, develop, deploy, manage and secure applications and solutions on public, private or hybrid cloud platforms

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  <div><strong>Imagine having an AI assistant at your fingertips</strong> that can understand complex documents and answer your questions accurately without requiring you to read through hundreds of pages. What if you could simply upload a technical report, legal document, or research paper and get precise answers based on its content? This is the power of combining <strong>multi-agent RAG systems with document intelligence</strong>.</div><div><br />In this hands-on lab, you'll build a sophisticated question-answering system that makes document comprehension accessible to everyone in your organization—from researchers analyzing technical papers to legal teams extracting insights from contracts, all without the tedious manual review.</div><div><br /></div><h1><strong>Project Overview</strong></h1><div>This lab teaches you to create an intelligent document processing system that handles the entire question-answering workflow:</div><div>1️⃣ <strong>Document Processing &amp; Chunking</strong> - Extract text from PDFs and other formats, process into searchable chunks with caching for performance<br />2️⃣ <strong>Hybrid Retrieval</strong> - Combine keyword-based BM25 and semantic vector search for optimal document retrieval<br />3️⃣ <strong>Multi-Agent Verification</strong> - Use specialized agents for relevance checking, research, and fact verification<br />4️⃣ <strong>LangGraph Orchestration</strong> - Coordinate agent interactions with conditional workflows and feedback loops</div><div><br />By connecting specialized agents through LangGraph, you'll create a seamless experience where users can upload documents and get verified, accurate answers using IBM's Granite AI's powerful models.</div><div><br /></div><h1><strong>What You'll Learn</strong></h1><div>By completing this lab, you will:</div><ul><li>Design effective <strong>document processing pipelines</strong> with caching and deduplication</li><li>Build <strong>hybrid retrieval systems</strong> that balance keyword precision with semantic understanding</li><li>Create <strong>specialized AI agents</strong> for different stages of the question-answering process</li><li>Implement <strong>verification mechanisms</strong> to ensure factual accuracy</li><li>Orchestrate <strong>complex workflows</strong> with conditional branching and feedback loops</li></ul><div><br /></div><h1><strong>Who Should Do This Lab</strong></h1><div>This project is ideal for:</div><ul><li><strong>Developers</strong> looking to build practical document intelligence applications</li><li><strong>Data scientists</strong> wanting to make document insights accessible to non-technical colleagues</li><li><strong>AI enthusiasts</strong> interested in creating trustworthy information retrieval systems</li></ul><div>No advanced ML expertise required—basic Python knowledge and curiosity about RAG applications are all you need.</div><div><br /></div><h1><strong>What You Need</strong></h1><div>✅ <strong>A browser</strong> to access the lab environment<br />✅ <strong>Basic Python knowledge</strong> (understanding functions and data structures)<br />✅ <strong>Basic LangChain and LLM knowledge</strong><br />✅ <strong>Sample documents</strong> (we provide examples, or bring your own PDFs)</div><div><br />By the end of this project, you'll have built an AI document assistant that transforms how people interact with information—enabling anyone to ask questions about complex documents and receive verified, accurate answers in seconds.</div>
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Multi-Agent RAG Smart Document QA with Docling & LangGraph

Build a multi-agent RAG document question-answering system using LangGraph workflows and Docling for document processing. Learn to extract content from PDFs with Docling, implement hybrid retrieval combining BM25 and vector search, and create specialized agents for relevance checking, research, and verification. Integrate with IBM WatsonX AI for embeddings and language models to generate accurate answers from documents. Master techniques for document chunking, caching, fact-checking responses, and handling complex questions through coordinated agent interactions.

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  <div><br />In this capstone course, you’ll demonstrate your ability to solve problems relevant to data-related roles, which you can then showcase in your portfolio and share with prospective employers. You will apply the skills you’ve learned throughout this data management program with this hands-on culminating project. </div><div><br />The project provides you the opportunity to solidify your proficiency when working with various aspects of data and integrate them into a single project. You’ll apply many industry-specific tools and industry-standard best practices to a real-world-inspired scenario. As part of this process, you utilize relational databases and SQL queries. You’ll also manipulate data using spreadsheets and BI tools to create visualizations and a dashboard to readily communicate your data insights. <br /><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Introduction and Data Preparation and Exploratory Analysis with Excel </strong></div><ul><li>Video: Course Introduction </li><li>Reading: Course Overview </li><li>Reading: Data Platform Architecture </li><li>Reading: Helpful Tips for Course Completion </li><li>Video: Assignment Overview: Data Cleaning &amp; Transformation Using Excel </li><li>Reading: Data Set Description </li><li>Lab 1: Data Cleaning &amp; Transformation </li><li>Checklist: Data Cleaning &amp; Transformation Using Excel  </li><li>Video : Assignment Overview: Data Visualization Using Excel </li><li>Lab 2: Data Visualization Using Excel </li><li>Checklist: Data Visualization Using Excel </li><li>Module 1: Summary and Highlights </li><li>Module 1 Graded Quiz: Data Preparation and Exploratory Analysis with Excel </li></ul><div><strong>Module 2: Relational Database (OLTP) </strong></div><ul><li>Video : Assignment Overview: Data Setup Using Relational Database </li><li>Lab 3: Data Setup Using Relational Database  </li><li>Checklist: Data Setup Using Relational Database </li><li>Video : Assignment Overview: Data Analysis with SQL </li><li>Lab 4: Data Analysis with SQL  </li><li>Checklist: Data Analysis with SQL  </li><li>Module 2: Summary and highlights </li><li>Module 2 Graded Quiz: Data Setup Using Relational Database (OLTP) </li></ul><div><strong> Module 3: Data Warehouse  </strong></div><ul><li>Video : Assignment Overview: Data Warehouse Design &amp; Setup </li><li>Lab 5: Data Warehouse Design &amp; Setup </li><li>Checklist: Data Warehouse Design &amp; Setup  </li><li>Video : Assignment Overview : Data Warehouse Analysis with SQL </li><li>Lab 6: Data Warehouse Analysis with SQL </li><li>Checklist: Data Warehouse Analysis with SQL </li><li>Module 3: Summary and Highlights </li><li>Module 3 Graded Quiz: Data Warehouse </li></ul><div><strong> Module 4: Data Privacy, Security, Governance, Risk, and Compliance </strong></div><ul><li>Video : Data Integration, Governance and Security Implementation for FinPro Bank </li><li>Reading: Recommendations on Integration, Governance and Compliance </li><li>Checklist: Data Privacy, Security, Governance, Risk, and Compliance </li><li>Video : Assignment Overview: Data Privacy, Security, Encryption, and Role-Based Access </li><li>Lab 7: Implementing Data Privacy, Security, Encryption, and Role-Based Access using MySQL </li><li>Checklist: Implementing Data Privacy, Security, Encryption, and Role-Based Access </li><li>Module 4: Summary and Highlights </li><li>Module 4 Graded Quiz: Data Privacy, Security, Governance, Risk, and Compliance </li></ul><div><strong> Module 5: Data Vizualization and Dashboard </strong></div><ul><li>Video: Assignment Overview: Business Intelligence Using Tableau </li><li>Lab: Business Intelligence Using Tableau </li><li>Checklist: Business Intelligence Using Tableau </li><li>Video: Assignment Overview: Story Dashboard </li><li>Lab 9: Story Dashboard </li><li>Checklist: Story Dashboard </li><li>Module 5: Summary and Highlights </li><li>Module 5 Graded Quiz: Data Visualization and Dashboards </li></ul><div><strong>Module 6: Final Submission &amp; Evaluation </strong></div><ul><li>Structure of a presentation</li><li>Best Practices for Presenting Your Findings</li><li>[Optional] Hands-on Lab: Getting started with PowerPoint for the web </li><li>[Optional] Hands-on Lab: Save Your PowerPoint Presentation as a PDF  </li><li>Reading: Final Project Instructions  </li><li>Assignment: Submit your work and review your peers </li><li>Reading: Congratulations &amp; Next Steps </li><li>Reading: Team and Acknowledgements </li><li>Video: Resume &amp; Job Search Tips </li><li>Reading: Guide to developing a Personal Portfolio </li><li>Video: Interview Preparation </li></ul><h1>What you'll learn</h1><ul><li>Integrate valuable applied data management skills employers need for a wide range of data-related roles in a culminating project. </li><li>Gain hands-on experience using industry-specific data tools including Excel, SQL, PostgreSQL, Tableau, etc.</li><li>Demonstrate best practices and apply those methodologies through industry-standard processes, data design, governance, security, and reporting.</li><li>Showcase your ability to solve problems relevant to working with data that you can discuss with colleagues and prospective employers.</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>We recommend that you complete all the previous courses in IBM Data Management Professional Certificate  before starting this course.</div><div><br /></div>
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Data Management Capstone Project

This capstone project underscores the vital role of a Data Manager in steering FinPro Bank toward a data-centric culture. By overseeing every aspect of the data management process—from data cleaning in Excel to building interactive dashboards in Tableau—the Data Manager ensures that data is accurate, secure, and accessible at each stage.

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  <div>This course will equip future Product Owners with the essential skills and strategies needed to maximize product value and drive innovation within Agile environments. This course includes a comprehensive exploration of topics such as product roadmaps, release planning, KPI development, and governance. As a result of this course, learners will be able to align product development with business goals.  <br /><br /></div><div>In this course, learners will explore the product owner role as part of product governance. They will learn that product owners’ responsibilities include ensuring the product delivers value while minimizing risks and maintaining accountability. They will gain the necessary knowledge to align product development with business goals. With regards to Agile, they will learn about the minimal viable product, or MVP, and how to develop the MVP to support the product vision by making use of the Scrum framework. You will learn how to track your Scrum team’s velocity to effectively balance strategic priorities and operational realities.  <br /><br /></div><div>The course also delves into technical practices, including acceptance testing, wireframing, and technical writing, which enable product owners to communicate effectively with stakeholders and development teams. The course also addresses technical debt, why it matters, and how a product owner can efficiently handle this debt by integrating its reduction strategically into sprints. <br /><br /><strong>Course Learning Objectives </strong></div><ul><li>Job-ready skills and tools needed for success in a Product Owner role  </li><li>Practical knowledge that transfers across industries that implement Scrum development teams  </li><li>Industry recognized strategies applicable to product development in an Agile environment  </li><li>Develop expertise for guiding Scrum teams to build products aligned with organizational goals  </li></ul><h1>Course Syllabus</h1><div><strong>Module 1: Introduction to Product Ownership and Strategic Foundations </strong></div><ul><li>Vdeo: Course Introduction</li><li>Reading: Course Overview</li><li>Video: Understanding the Product Owner Role  </li><li>Reading: Product Owner Skills Checklist  </li><li>Expert Viewpoint: Role of the Product Owner  </li><li>Video: Product Value Maximization  </li><li>The Product Owner's Impact on Value Delivery  </li><li>Practice Quiz  </li><li>Video: Eliciting Requirements  </li><li>Video: Scenario Development  </li><li>Video: Technical Debt Management  </li><li>Expert Viewpoint: Managing Technical Debt  </li><li>Lab/Activity: Technical Debt  User Stories </li><li>Practice Quiz:</li><li>Reading: Module 1 Summary and Highlights  </li><li>Module 1 Glossary</li><li>Module 1 Graded Quiz </li></ul><div><strong>Module 2: Product Planning, Roadmaps, and Metrics  </strong></div><ul><li>Video: Governance Planning and Budgeting  </li><li>Expert Viewpoint: Role of the Product Owner in Strategic Planning  </li><li>Demo Video: Lean Canvas Planning  </li><li>Lab: Lean Canvas Creation  </li><li>Video: KPI Development and Management  </li><li>Practice Quiz</li><li>Demo Video: Product Roadmaps  </li><li>Reading: Scaling Agile Frameworks </li><li>Video: Release Planning  </li><li>Expert Viewpoint: Agile Scaling and Product Release Planning</li><li>Demo Video: Release Planning Example  </li><li>Lab: Network Diagramming Method  </li><li>Practice Quiz </li><li>Reading: Module 2 Summary and Highlights  </li><li>Module 2 Glossary</li><li>Graded Quiz</li></ul><div><strong>Module 3: Agile Practices, Technical Skills, and Communication </strong></div><ul><li>Video: Technical Writing and Communication  </li><li>Expert Viewpoint: Tips for effective technical writing  </li><li>Demo Video: Persona Development  </li><li>Video: Acceptance Testing and UX Integration  </li><li>Video: Managing Customer Feedback  </li><li>Practice Quiz  </li><li>Reading: Product Management Lifecycle Overview  </li><li>Video: Working with Product Management Lifecycle  </li><li>Video: Effective Product Owner and Product Manager collaboration tips  </li><li>Demo Video: Velocity Management and Estimation Techniques  </li><li>Lab: Velocity Planning</li><li>Video: Plan velocity based on a scenario</li><li>Wireframes, Mock-ups, and Prototypes  </li><li>Video: Using Visual Tools to Communicate Product Vision  </li><li>Practice Quiz </li><li>Reading: Module 3 Summary and Highlights  </li><li>Module 3 Glossary</li><li>Graded Quiz</li></ul><div><strong>Module 4: Guided Project, Final Assessment, and Course Wrap-Up </strong></div><ul><li>Reading: Final Project Overview  </li><li>Final Project: AutoproSolutions Inc,</li><li>Final Quiz</li><li>Video: Course Wrap-Up  </li><li>Reading: Congratulations and Next Steps  </li><li>Reading: Thanks From the Course Team  </li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>Some experience or familiarity with product development processes or related roles, Exposure to Agile-related concepts and terms </div>
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Product Owner: Essential Skills and Tools for Innovation

Product Owners play a critical role in ensuring the success of products and the realization of business value in an increasingly complex and competitive landscape.  This course teaches prospective Product Owners essential skills and strategies that drive product innovation within Agile environments, such as product roadmaps and key performance indicators. 

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  <div>Collaboration and communication are at the core of a Product Owner's function in driving product success. Communicating effectively is essential in handling stakeholders, building collaboration, and delivering customer value. </div><div><br />This course is perfect for those in product owner roles.  Whether you are new to Agile or sharpening your expertise: <br /><br /> - Explore Agile and Scrum frameworks to manage team dynamics and stakeholder needs. <br /><br /> - Learn to break down requirements into epics, user stories, and acceptance criteria. <br /><br /> - Discover advanced tools for virtual collaboration, conflict resolution, and global team management. <br /><br /> - Develop techniques for prioritizing deliverables, managing trade-offs, and protecting the Voice of the Customer (VOC). <br /><br /> - Master the key communication models and practices <br /> <br />Through exercises and expert insights, develop: <br /><br /> - Collaborative workshop facilitation. <br /><br /> - Skills in managing product backlogs and deliverables. <br /><br /> - Strategies for working with cross-functional teams, DevOps, and diverse communication styles. <br /> <br />By the end of this course, you'll confidently apply collaboration, negotiation, and communication strategies to manage products effectively in complex team environments. Enroll soon to elevate your skills and drive product success!<br /><br /></div><div><strong>You will learn:</strong> </div><ul><li>Effective communication strategies to represent the Voice of the Customer within Agile teams and organizations. </li><li>Stakeholder engagement strategies to gather feedback, validate assumptions, make effective decisions, and influence results.  </li><li>Negotiation and conflict resolution skills to navigate competing priorities and viewpoints effectively. </li><li>Facilitation and leadership skills to effectively lead product discovery sessions, collaborative workshops, and decision-making processes. </li></ul><h1>Course Syllabus</h1><div><strong>Module 1: Foundations of Collaboration</strong></div><ul><li>Video: Course Introduction </li><li>Reading: Course Overview</li><li>Reading: How to Make the Most from this Course </li><li>Video: Define the Communications Model</li><li>Expert Viewpoints Video: Meet the Experts</li><li>Lab: Collaboration and Product Vision</li><li>Video: The Need for Effective Communications Planning</li><li>Expert Viewpoints: Communications: Significance of Planning</li><li>Demo Video: Communication Matrix: Best Practices and Product Owner’s Role</li><li>Practice Quiz: Foundations of Collaboration</li><li>Expert Viewpoints: The Importance of Communication and Collaboration </li><li>Summary and Highlights: Foundations of Collaboration</li><li>Graded Assignment: Graded Quiz: Foundations of Collaboration</li></ul><div><strong>Module 2: Advanced Techniques in Collaboration and Product Development </strong></div><ul><li>Video: Elements of a Cross-Functional Team</li><li>Video: Team Development and Management Objectives</li><li>Reading: The 5 Dysfunctions of a Team Overview by Patrick Lencioni</li><li>Reading: How a Product Owner Interacts with the Scrum Team</li><li>Video: Developing an Agile Mindset  </li><li>Reading: Compare and Contrast Program Management Frameworks</li><li>Video: Breaking Down Requirements</li><li>Lab: Breaking Down Requirements </li><li>Reading: Quick Overview of the INVEST Model for Creating Good User Stories</li><li>Expert Viewpoints: Using Models and Guidelines (Reality versus Theory)</li><li>Video: Balancing the Needs of Scrum Team, Stakeholders, and Customers</li><li>Practice Quiz: Setting the foundation for Scrum (Team Dynamics, Agile Mindset, Stakeholders) Video: Kotler’s Five Levels of a Product </li><li>Video: Mastering Conflict Resolution: Five Conflict Management Styles</li><li>Lab: Scenarios of Conflict and Negotiation (Practice)</li><li>Reading: Overview of Key Marketing Needs (Collateral, Value, Velocity)</li><li>Video: Product Owner Collaboration Strategies Beyond Agile Team</li><li>Reading: Summary of the 4-Steps to Gathering and Validating Requirements</li><li>Video: Eliciting and Validating Requirements</li><li>Lab: Using the Tuckman Ladder Model to Help Prepare for Technical Readiness</li><li>Demo Video: RACI Matrix: A Guide to Effective Stakeholder Management in Agile Projects</li><li>Practice Quiz: Understanding Roles and Styles in Negotiation</li><li>Reading: Summary and Highlights: Advanced Techniques in Collaboration and Product Development </li><li>Graded Assignment: Advanced Techniques in Collaboration and Product Development </li></ul><div><strong>Module 3: Managing Product Deliverables Through Effective Collaboration </strong></div><ul><li>Reading: Methods and Tools Used to Prioritize Requirements (MoSCoW, Weighted Matrix, Dot Voting, etc)</li><li>Video: Interconnection Between Prioritization and Product Backlog</li><li>Lab: Working with Tradeoffs in Product Backlog Management</li><li>Lab: Sharing Status Updates as a Product Owner</li><li>Video: Product Owner Responsibilities in Knowledge and Document Management</li><li>Expert Viewpoints Video: Working with Global Teams and Virtual Collaboration</li><li>Reading: Survey of Tools and Methods for Virtual Collaboration (Pros and Cons)</li><li>Lab: Collaboration, Engagement, and Accountability in Global and Virtual Environments</li><li>Practice Quiz: Tools, Techniques, and Models to Manage Product Deliverables</li><li>Video: Effective Collaboration with DevOps and Scrum Master </li><li>Reading: Survey of Collaborative Problem-Solving Techniques (Pros and Cons)</li><li>Video: Managing Conflict During Problem-Solving  Discussions</li><li>Reading: Designing and Facilitating Collaborative Workshops</li><li>Lab: Planning and Facilitating Collaborative Workshops</li><li>Video: Communication Styles</li><li>Expert Viewpoints Video: Managing Conflicts and Communication Styles (Pros and Cons)</li><li>Lab: Working Effectively with Four Communication Styles</li><li>Practice Quiz: Understanding and Working with Different Perspectives</li><li>Reading: Summary and Highlights: Managing Product Deliverables Through Effective Collaboration</li><li>Graded Assignment: Graded Quiz: Managing Product Deliverables Through Effective Collaboration</li></ul><div><strong>Module 4: Final Project and Assessment</strong></div><ul><li>Final Project: Mastering Product Ownership</li><li>Final Project Submission </li><li>Expert Viewpoints: Navigating Different Roles and Styles</li><li>Course Glossary</li><li>Final Quiz</li><li>Video: Course Wrap-up </li><li>Reading: Congratulations and Next Steps</li><li>Reading: Team and Acknowledgments</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>This course requires no prior experience and is suitable for anyone aspiring to pursue a career in product management. </div>
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Product Owner: Communications & Stakeholder Management

Gain hands-on experience with communication, collaboration, and business skills to engage stakeholders and manage products. Apply this knowledge to evaluate case studies effectively. 

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  <div><br />Unleash your career potential with our course on the fundamentals of the Scrum Master role. Whether you're new to Agile methodologies or seek to enhance your project management skills, this course will equip you with the knowledge and tools needed to excel as a Scrum Master. <br /><br /></div><div><br />Throughout the course, you'll learn the essential aspects of being a Scrum Master. By contrasting Scrum with traditional project management methods, you'll gain a deep understanding of why Scrum is a game-changer in today's dynamic business landscape. <br /><br />We also dive into the practical skills required to become a highly effective Scrum Master. Through hands-on practice and real-life scenarios, you'll develop your abilities to navigate challenges, foster collaboration, and drive successful project outcomes.  <br /><br />Although this course is beneficial for learners who are already project managers, it is not essential for them to have project management experience. <br /><br />With engaging video content and interactive exercises, you'll find yourself immersed in the world of Scrum. The course is designed to prepare you for the final exam, designed to simulate the certification exams you may encounter. Gain the confidence and experience you need to ace those tests and prove your expertise as a Scrum Master.<br /><br /></div><div><strong>What You'll Learn</strong></div><ul><li>Summarize the role of the Scrum Master to include a position description, benefits of the position, and key skills essential to success. </li><li>Compare and contrast the role of the Scrum Master to a traditional project manager. </li><li>Describe opportunities for Scrum Masters in the current work environment to include potential employment, job requirements, and salary ranges. </li><li>Define certification opportunities in Agile and Scrum to include Scrum Alliance CSM, PMI-ACP, and PMI-DASM. </li></ul><h1>Course Syllabus</h1><div>Module 1: The Role of the Scrum Master </div><ul><li>Video: Course Introduction: Scrum Master Profession</li><li>Reading: Course Overview: Scrum Master Profession</li><li>Reading: How to make the most from this course</li><li>Reading: Module Overview</li><li>Video: Scrum Master Role and Benefits </li><li>Video: Expert Viewpoints: What Does the Scrum Master Do? </li><li>Video: Scrum Master Skill Inventory </li><li>Video: Expert Viewpoints: Scrum Master Skills  </li><li>Video: A Day in the Life of a Scrum Master </li><li>Reading: Adaptive Methodologies </li><li>Lab: Case Study: The Role of a Scrum Master </li><li>Reading: Module 1 Summary: The Role of the Scrum Master </li><li>Practice Quiz: Module 1: The Role of the Scrum Master </li><li>Reading: Module 1 Glossary: The Role of the Scrum Master  </li><li>Graded Quiz: Module 1: The Role of the Scrum Master  </li></ul><div>Module 2: Scrum Master Opportunities </div><ul><li>Reading: Module 2 Overview and Key Takeaways</li><li>Video: Scrum Master and Traditional Project Manager Comparison  </li><li>Video: Expert Viewpoints: Scrum Master Opportunities </li><li>Video: Developing Scrum Master Skills </li><li>Video: Scrum Master Employment Opportunities </li><li>Video: Scrum Master Levels </li><li>Video: Expert Viewpoints: Why Become a Scrum Master </li><li>Lab: Potential Scrum Master Job Opportunities  </li><li>Reading: Module 2 Summary: Scrum Master Opportunities  </li><li>Practice Quiz: Module 2: Scrum Master Opportunities  </li><li>Reading: Module 2 Glossary: Scrum Master Opportunities  </li><li>Graded Quiz: Module 2: Scrum Master Opportunities  </li><li>Discussion Prompt: Are you now more or less motivated to pursue the role of Scrum Master? Why?</li></ul><div>Module 3: Scrum Master Job Overview and Opportunities </div><ul><li>Reading: Module 3 Overview </li><li>Reading: Module 1 and 2  Review and Key Takeaways </li><li>Video: Expert Viewpoints: Scrum Master Employment </li><li>Video: The Path to Certification PMI-ACP, PMI-DASM, and CSM  </li><li>Video: Expert Viewpoints: Scrum Master Job Environment </li><li>Reading: Module 3 Glossary: Scrum Master Job Overview and Opportunities   </li><li>Practice Assessment: Scrum Master Job Overview and Opportunities  </li><li>Reading: Course Glossary  </li><li>Graded Assessment: Scrum Master Job Overview and Opportunities  </li></ul><div>Module 5: Final Project  </div><ul><li>Reading: Final Project Overview </li><li>Lab: Project Scenario </li><li>Lab: Exercise 1: Perform a SWOT Analysis </li><li>Lab: Exercise 2: Take Action Based on SWOT Analysis </li><li>Final Project: Submission and Evaluation</li><li>Video: Expert Viewpoints: Advice for Aspiring Scrum Masters </li><li>Reading: Congratulations and Next Steps </li><li>Reading: Thanks from the Course Team </li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>This aspiring Scrum Master should possess some basic project management skills and experience. However, experience is not mandatory.  industries worldwide! </div>
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Introduction to Scrum Master Profession

Kick-start your Scrum Master journey and build an essential understanding of the role. 

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  <div>This course provides a comprehensive introduction to the transformative role of generative artificial intelligence (AI) in mobile app development. You will learn how to leverage generative AI across the app development lifecycle, including design, content generation, marketing, and user support. Through hands-on labs, engaging video lectures, and interactive quizzes, you will gain practical experience with leading AI tools like Claude AI, Copy.ai, and Apple Intelligence.<br /><br />The course begins with exploring generative AI concepts, focusing on its applications in app design, gaming, and user engagement. It also addresses the opportunities and challenges in using AI for personalized marketing and support. Then, you’ll dive deeper into advanced topics, such as machine learning models, embedded AI, and cloud-based development tools.<br /><br />By the end of the course, you will create a functional mobile app prototype, integrating generative AI features to enhance user experience. This course equips you with the skills to innovate in the rapidly evolving field of mobile technology, preparing you for roles in development, marketing, and beyond.</div><h1>Course Syllabus</h1><div><a href="https://gbc-word-edit.officeapps.live.com/we/wordeditorframe.aspx?ui=en-US&amp;rs=en-US&amp;IsLicensedUser=0&amp;WOPISrc=https%3A%2F%2Fapi.box.com%2Fwopi%2Ffiles%2F1593824934576#_Toc170240805"><strong>Module 1: Introduction to Generative AI for Mobile App</strong></a><strong> Development</strong> </div><ul><li>Video: Course Introduction </li><li>Reading: Course Overview </li><li>Reading: Helpful Tips for Course Completion </li><li>Video: Opportunities and challenges of Gen AI in mobile apps  </li><li>Video: Designing Mobile Apps using Gen AI  </li><li>Lab: Generate a quick prototype using Uizard </li><li>Video: Content creation using Gen AI for Mobile Apps </li><li>Lab: Generate a splash screen using Claude AI </li><li>Video: Transforming Gaming and AR/VR mobile apps with Gen AI </li><li>Demo Video: Exploring AR/VR mobile apps </li><li>Reading: Best practices for incorporating Gen AI in mobile design </li><li>Practice Quiz: Generative AI in Mobile App Development  </li><li>Video: Gen AI for mobile app Marketing  </li><li>Lab: Create a marketing campaign using copy.ai </li><li>Video: Gen AI for mobile app support </li><li>Lab: Creating a FAQ using Synthesia.io </li><li>Video: Gen AI for behavioral analysis and customization </li><li>Reading: Industry use cases of Gen AI in Mobile Apps </li><li>Practice Quiz: Generative AI for Mobile Marketing and Support </li><li>Reading: Summary and Highlights: Introduction to Generative AI for Mobile App Development </li><li>Graded Quiz: Introduction to Generative AI for Mobile App Development </li></ul><div><strong>Module 2:  Generative AI Tools for Mobile Development </strong></div><ul><li>Video: Generative AI for Cutting-Edge Android Apps </li><li>Demo video: Vertex AI Studio</li><li>Lab: Leverage Dialogflow for creating a Retail order assistant chatbot</li><li>Video: Elevate iOS Apps with Generative AI  </li><li>Demo video: Introducing Apple Intelligence </li><li>Reading: Developing with Apple Intelligence (Beta) </li><li>Practice Quiz: Generative AI Tools for Mobile Development </li><li>Video: Building intelligent Mobile apps with Machine Learning models  </li><li>Demo Video: AI Lifecycle platform - Clarifai</li><li>Video: AI powered IDEs for Mobile App development</li><li>Demo video: Exploring Project IDX </li><li>Lab: Creating a React Native app with Project IDX and Gemini AI for a Dynamic Form</li><li>Reading: Leveraging Custom AI models in cloud Mobile app Development </li><li>Practice Quiz: Advanced concepts for Gen AI in Mobile Apps</li><li>Reading: Summary and Highlights: Generative AI tools for Mobile development  </li><li>Graded Quiz: Generative AI tools for Mobile development </li></ul><div><a href="https://gbc-word-edit.officeapps.live.com/we/wordeditorframe.aspx?ui=en-US&amp;rs=en-US&amp;IsLicensedUser=0&amp;WOPISrc=https%3A%2F%2Fapi.box.com%2Fwopi%2Ffiles%2F1593824934576%22%20\l%20%22_Toc170240809"><strong>Module 3: Final Project, Final Exam and Course Wrap-Up</strong></a> </div><ul><li>Reading: Final Project Overview </li><li>Final Project: Smart Health App </li><li>Video: Course Wrap-Up </li><li>Reading: Useful Prompts for mobile app developers</li><li>Reading: Course Glossary </li><li>Reading: Congratulations and Next Steps </li><li>Reading: Thanks from the Course Team </li></ul><div><strong>What you'll learn</strong></div><ul><li>Understand generative AI concepts for mobile app development</li><li>Analyze opportunities and challenges in AI-driven app design and marketing</li><li>Demonstrate proficiency with AI tools like Vertex AI, Dialogflow, and Apple Intelligence</li><li>Build a mobile app prototype using generative AI tools</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>Learners will need a desktop or laptop computer with a modern web browser and a reliable internet connection. </div>
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Generative AI: Turbocharge Mobile App Development

This course will explore the transformative potential of generative artificial intelligence in mobile app development. You will learn how to integrate AI tools and frameworks to enhance app design, marketing, and user engagement. As you progress through the course, you will gain insights into the opportunities and challenges of using generative AI in areas such as gaming, augmented reality, and virtual reality. You will also develop the skills to leverage advanced AI-driven solutions to build innovative mobile applications.

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  <div>Improve your front-end development skills by learning one of the most popular front-end frameworks, React, using ES6 in this hands-on course. This course is for you if you want to take the next step in your front-end development journey. </div><div> </div><div>In this course, you will build rich front-end applications with React and ES6 JavaScript specifications. You will learn JSX, a JavaScript extension that allows you to write HTML-like code embedded into your JavaScript code, easily allowing you to create React elements. You create these elements with React components and learn how to manipulate the components using the props (properties) and event handling. Then, you explore ways to pass data and states between components by understanding the  lifecycle. </div><div> </div><div>You will investigate advanced topics like “hooks,” allowing you to write readable, testable, and maintainable code more efficiently. You round out this class learning about the “Redux” library, which helps you write applications in different environments, allowing you to build complex, interactive React applications more easily.  </div><div>Throughout the course, you will build your portfolio by completing numerous hands-on labs to gain practical experience. At the end of the course, you pull together what you’ve learned with a final project by building a budgeting allocation application. <br /><br /></div><div>This course will help you succeed as a front-end or full-stack developer. It suits those in IT looking to step up in their careers or new graduates seeking to establish their client-side skills. To be successful in this course, you will need basic HTML, CSS, JavaScript, and Git skills. <br /><br /></div><h1>What You'll Learn</h1><ul><li>Write interactive applications using the React web framework. </li><li>Build React elements using JSX and React components. </li><li>Communicate and exchange data with external services using GET, POST, UPDATE, and DELETE requests. </li><li>Use props, states, and hooks to pass data and manipulate the states of React components. </li></ul><h1>Prerequisites</h1><div>Basic knowledge of HTML, CSS, JavaScript, and Git <br /><br /></div><h1>Course Syllabus</h1><div>Module 1: Building Rich Front-End Applications with React and ES6 </div><ul><li>Introduction to Front-End Frameworks and React </li><li>Insiders Viewpoints: Front-end Frameworks </li><li>Introduction to ES6 </li><li>Introduction to JSX </li><li>Hands-on Lab: Hello World with React </li><li>Introduction to Components </li><li>React Components - Props and Event Handling </li></ul><div><br />Module 2: React Components </div><ul><li>Introduction to States </li><li>Passing data and states between components </li><li>Components Lifecycle </li><li>Testing React Components </li><li>Hands-on Lab: React Todo List Application </li></ul><div><br />Module 3: Advanced React </div><ul><li>Hooks </li><li>Implementing Forms </li><li>Introduction to Redux </li><li>Essential Concepts of Redux  </li><li>Async with Redux </li><li>Binding Redux and Flow </li><li>Hands-on Lab: React Redux </li></ul><div><br />Module 4: Final Project </div><ul><li>Hands-on Lab: Budget Allocation Application </li><li>Optional Sample Project: The Shopping Application </li><li>Final Project: Budgeting Allocation Application </li></ul>
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Developing Front End Apps with React

Learn to build rich Front-End apps with React and ES6, connect components, write advanced components, and test them. Plus, a final project to add to your portfolio.

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  <div>This course is designed for enthusiasts and practitioners who share an interest in the rapidly advancing field of generative AI.<br /><br /></div><div>This course centers around the core concepts and generative AI models that form the building blocks of generative AI. You will delve into the concepts of deep learning and large language models (LLMs). You will learn about GANs, VAEs, transformers, and diffusion models – the fundamental components of generative AI.<br /><br /></div><div>You will learn about the concept of foundation models. You will gain insights into the capabilities of pre-trained models and platforms for AI application development. The course will also cover how foundation models utilize these platforms to generate text, images, and code. Additionally, participants will explore various generative AI platforms such as IBM watsonX and Hugging Face.<br /><br /></div><div>The course includes practical hands-on labs, offering participants the chance to delve into the applications of generative AI using the IBM Generative AI Classroom and platforms like IBM watsonX. Throughout the course, you'll have the opportunity to explore various models, including IBM Granite, OpenAI GPT, Google Flan, and Meta Llama. Additionally, expert practitioners will share insights into the capabilities, applications, and tools of generative AI. <br /><br /><strong>What you'll learn</strong></div><ul><li>Describe the fundamental concepts of generative AI.</li><li>Explore the building blocks of generative AI, including GANs, VAEs, transformers, and diffusion models.</li><li>Explain the concept of foundation models in generative AI.</li><li>Explore the ability of foundation models to generate text, images, and code using pre-trained models.</li><li>Describe the features, capabilities, and applications of different generative AI platforms, including IBM Watson and Hugging Face.</li></ul><h1>Course Syllabus</h1><div><strong>Module 1: Models for Generative AI</strong></div><ul><li>Video: Course Introduction</li><li>Reading: Course Overview</li><li>Reading: Program Overview</li><li>Reading: Helpful Tips for Course Completion</li><li>Video: Deep Learning and Large Language Models</li><li>Video: Generative AI Models</li><li>Video: Foundation Models</li><li>Labs: Generative AI Foundation Models</li><li>Expert Viewpoints Video: Advancing Generative AI Capabilities</li><li>Expert Viewpoints Video: Exploring Generative AI Capabilities of IBM Watsonx</li><li>Reading: Module Summary</li><li>Practice Quiz: Core Concepts and Models of Generative AI</li><li>Discussion Prompt: Working with Foundation Models</li><li>Reading: IBM Granite Foundation Models</li><li>Graded Quiz: Models for Generative AI</li></ul><div><strong>Module 2: Platforms for Generative AI</strong></div><ul><li>Video: Pre-trained Models: Text-to-Text Generation</li><li>Lab: Develop AI Applications with the Foundation Models</li><li>Video: Pre-trained Models: Text-to-Image Generation</li><li>Video: Pre-trained Models: Text-to-Code Generation</li><li>Lab: Develop AI Applications for Code Generation</li><li>Video: IBM Watsonx.ai</li><li>Reading: IBM Watsonx. data and Watsonx. governance</li><li>Video: Hugging Face</li><li>Expert Viewpoints Video: Fostering Innovation through Hugging Face</li><li>Reading: Module Summary</li><li>Practice Quiz: Pre-trained Models and Platforms for AI Applications Development</li><li>Graded Quiz: Platforms for Generative AI</li></ul><div><strong>Module 3: Course Quiz and Final Project</strong></div><ul><li>Reading: Module Introduction and Learning Objectives</li><li>Glossary - Generative AI: Foundation Models and Platforms</li><li>Final Project: Working with IBM Granite Foundation Models</li><li>Final Exam: Graded Quiz: Generative AI: Foundation Models and Platforms</li></ul><div><strong>Course Wrap-Up</strong></div><ul><li>Reading: Congratulations and Next Steps</li><li>Reading: Thanks from the Course Team</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>This course is for anyone wanting to learn and get familiar with the concepts of generative AI. No prior knowledge is required for this course. Note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.</div>
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Models and Platforms for Generative AI

Understanding the core concepts and foundational models of generative AI gives you the footing that you need in the rapidly developing field of generative AI, which is transforming our world. Along with deep learning and LLMs, you'll explore GANs, VAEs, transformers, and diffusion models, which are the building blocks of generative AI. This course is for all enthusiasts and practitioners with an interest in learning what generative AI is and how it works.

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  <div>In today's rapidly evolving AI landscape, AI systems often produce inconsistent, unpredictable outputs when multiple agents need to communicate with each other. When one agent's output becomes another's input, the lack of structure leads to cascading errors, misinterpretations, and unusable results. This guided project addresses this fundamental challenge by showing you how to enforce structured data exchanges between AI agents.<br /><br /></div><div>You'll learn how to ensure consistent, structured outputs from AI agents - a common challenge in AI development. Working with a research report scenario, you'll build a system that transforms unstructured AI responses into professional documents.<br /><br /></div><div>You'll design hierarchical data models with Pydantic as blueprints for your AI outputs, then create specialized CrewAI agents with distinct roles: a researcher, an analyst, and a formatter. You'll coordinate these agents in a workflow where each agent's output becomes structured input for the next, using data models to eliminate inconsistencies. By the end, you'll have a reusable framework for generating well-structured reports on any subject, automating what would normally take days of manual work into a process that produces professional results within hours.</div><div><br /><br /></div><h1>What You'll Learn</h1><div>By completing this lab, you will:</div><ul><li>Create structured data models using Pydantic to enforce consistency in LLM outputs</li><li>Design specialized AI agents with specific roles using CrewAI</li><li>Implement multi-stage workflows that transform research into organized documents</li><li>Build hierarchical data structures for proper validation and formatting</li><li>Generate professional reports with consistent formatting and citations</li><li>Apply data validation techniques to prevent incomplete LLM outputs</li></ul><div><br /></div><h1>Who should enroll</h1><div>This project is perfect for:</div><ul><li>AI developers looking to build more reliable agent-based systems</li><li>Data scientists who need to generate consistent reports from AI research</li><li>Software engineers interested in structured data handling with AI</li><li>Business analysts wanting to automate research and reporting workflows</li></ul><div><br /></div><h1>What you'll need</h1><div>Before beginning this guided project, you should have:</div><ul><li>Basic understanding of Python programming</li><li>Access to a modern web browser for the IBM Skills Network Labs environment</li></ul><div><br /></div><h1>Why enroll</h1><div>The ability to create AI systems that produce structured, consistent outputs is increasingly critical as organizations move AI from experimentation to production. By learning to enforce data models and orchestrate specialized agents, you'll gain valuable skills for building reliable AI applications that deliver professional results in research, content generation, and data analysis.</div><div><br /></div>
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Structuring LLM Outputs with CrewAI and Pydantic for Agents

Transform chaotic LLM outputs into consistent, professional documents by implementing structured data models with Pydantic and multi-agent workflows in CrewAI. This project teaches you to design specialized AI agents that collaborate to research topics and generate formatted reports, ensuring reliable outputs regardless of the subject matter. By creating a hierarchical data architecture that enforces validation and formatting rules, you'll learn to build AI systems that consistently deliver client-ready documents with proper structure, citations, and visual formatting.

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  <div>What separates sophisticated AI from basic models? The ability to critique and improve its own work. In this guided project, you'll learn how to implement reflection agents using LangGraph—AI systems that evaluate their outputs, identify weaknesses, and iteratively enhance their responses without human intervention.<br /><br /></div><div>You'll construct a complete workflow that mimics the human creative process: generate content, step back to evaluate it, then revise based on deliberate feedback. Working with a practical LinkedIn post generation example, you'll witness how reflection transforms basic AI responses into polished, engaging content through multiple refinement cycles.<br /><br /></div><div>This project reveals the architecture behind self-improving agentic AI systems, giving you hands-on experience with one of the most important advancements in modern AI development—the ability to implement artificial "System 2" thinking where deliberate reflection leads to superior results.<br /><br /></div><h1><strong>What you'll learn</strong></h1><div>After completing this project, you will be able to:</div><ul><li><strong>Design reflection workflows</strong> with LangGraph that enable AI to critique and improve its own outputs</li><li><strong>Implement generation, evaluation, and refinement stages</strong> in a connected agentic system</li><li><strong>Create feedback mechanisms</strong> that allow AI to objectively assess its content quality</li><li><strong>Build conditional logic</strong> to control when reflection cycles should continue or end</li><li><strong>Apply reflection principles</strong> to various AI applications beyond the project examples</li></ul><div><br /></div><h1><strong>Who this project is for</strong></h1><div>This project is perfect for:</div><ul><li><strong>Software developers</strong> seeking to build more sophisticated and reliable systems</li><li><strong>Data scientists</strong> working with large language models</li><li><strong>ML engineers</strong> interested in self-improving agentic AI applications</li><li><strong>Content creators</strong> looking to leverage AI with refinement capabilities</li></ul><div><br /></div><h1><strong>What you'll need</strong></h1><div>Before beginning this guided project, you should have:</div><ul><li>Basic understanding of Python programming</li><li>Familiarity with LLM concepts and applications</li><li>Access to a modern web browser for the IBM Skills Network Labs environment</li></ul><div><br /></div><h1><strong>Why enroll</strong></h1><div>By the end of this project, you'll possess the skills to build AI systems that think twice—generating content and then critically reviewing it before delivering final results. This reflection capability is the key difference between basic AI applications and truly intelligent systems. Whether you're developing content generators, virtual assistants, or analytical tools, incorporating reflection mechanisms with LangGraph dramatically improves output quality and reliability. Join this project to learn how to transform one-shot AI responses into thoughtful, refined content through the power of self-critique and iteration.</div>
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Make Your AI Agents Smarter with Reflection in LangGraph

Build AI Agents that reason, critique their own work, and iteratively improve their responses just like a human. This project teaches you to build a LinkedIn post optimization workflow where content improves with each iteration, just like human editing. In just 45 minutes, master the principles of reflection agents that can recognize their own limitations and actively improve their responses—an essential skill for creating more intelligent, agentic AI systems.

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  <div>Language models become dramatically more powerful when they can interact with external services and data. In this hands-on guided project, you'll learn how to build this critical bridge between AI and the digital world through custom tool development.<br /><br /></div><div>Using YouTube content analysis as our example, you'll create specialized tools that enable language models to perform actions they couldn't accomplish alone. You'll build functions that extract video IDs, fetch transcripts, search for content, retrieve metadata, and access trending videos—giving your AI assistant comprehensive media analysis capabilities.<br /><br /></div><div>The project focuses on manual tool calling—controlling how LLMs select and execute tools. You'll learn how language models decide which tools to use, how to extract their requests, execute the appropriate functions, and return results in the expected format. This understanding is essential for debugging, customization, and building reliable AI systems.</div><div><br /></div><h1><strong>What you'll learn</strong></h1><div>After completing this project, you will be able to:</div><ul><li>Design custom tools with proper documentation, type hints, and error handling</li><li>Understand how LLMs select appropriate tools based on user requests</li><li>Extract tool call information from LLM responses</li><li>Execute tool calls manually with correct parameter formatting</li><li>Structure and manage conversations that include multiple tool calls</li><li>Build organized tool mappings for complex applications</li><li>Implement chains that handle multi-step tool execution workflows</li></ul><div><br /></div><h1><strong>Who should enroll</strong></h1><div>This project is perfect for:</div><ul><li>AI developers seeking to extend language model capabilities</li><li>Software engineers building LLM-powered applications</li><li>Data scientists interested in programmatic content analysis</li><li>Technology professionals implementing practical AI solutions</li><li>Content creators looking to automate YouTube data collection</li></ul><div><br /></div><h1><strong>What you'll need</strong></h1><div>Before beginning this guided project, you should have:</div><ul><li>Basic understanding of Python programming</li><li>Familiarity with language models and their capabilities</li><li>Access to a modern web browser for the IBM Skills Network Labs environment</li><li>Optional: Prior experience with LangChain is helpful but not required</li></ul><div><br /></div><h1><strong>Why enroll</strong></h1><div>By the end of this project, you'll understand the mechanics behind today's most advanced AI assistants. The ability to create custom tools and control their execution is what separates basic chatbots from powerful AI systems that can search databases, analyze content, and interact with external services.<br /><br /></div><div>As organizations increasingly adopt AI solutions, the demand for developers who understand tool integration continues to grow. Whether you're building research assistants, content analysis tools, or customer service agents, mastering custom tool development will enable you to create AI applications that deliver real-world value by combining the reasoning capabilities of language models with access to specialized functions and external data sources.</div>
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Build and Execute Your Own Tools for LLMs

Connect language models to the digital world by building tools that serve as their hands and eyes. This project shows you how to create specialized functions that let LLMs interact with YouTube videos and external services. You'll master the process of designing tools and controlling their execution through manual tool calling. Learn to build functions that extract video IDs, fetch transcripts, and analyze trending content. In just 1 hour, gain the expertise to create AI systems that search and analyze video content and understand the mechanics behind today's most powerful AI assistants.

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  <div>Learn to implement agentic workflows with LangGraph and discover how to build intelligent AI agents capable of making dynamic, context-aware decisions. This guided project will walk you through the core components of LangGraph, including nodes, states, edges, and conditional edges, to help you create flexible and autonomous systems. You’ll learn how to design and implement sophisticated workflows, such as user authentication systems, that adapt to different scenarios based on success, failure, or conditional logic.  <br /><br /></div><div>Through hands-on exercises, you’ll gain a deep understanding of how each component works and how to connect them to design seamless decision-making workflows. Whether you’re managing state transitions, setting up dynamic conditions, or creating failure-handling mechanisms, this project will empower you to create advanced AI systems with high levels of flexibility and autonomy.<br /><br /></div><div><strong>What You’ll Learn<br /></strong><br /></div><ul><li><strong>LangGraph Essentials</strong>: Understand the key components—nodes, states, edges, and conditional edges—that power decision-making in AI systems.</li><li><strong>Dynamic Workflows</strong>: Learn how to build user authentication systems and other workflows with flexible decision logic, tailored to different user states and conditions.</li><li><strong>State-driven Logic</strong>: Explore how to manage state transitions and conditional logic to ensure smooth execution of tasks, handling both success and failure scenarios.</li><li><strong>Building Autonomous Systems</strong>: Develop skills to create autonomous agents that adapt based on real-time inputs, making intelligent decisions that reflect changing conditions.</li></ul><div><br /></div><div><strong>Why It Matters</strong><br /> LangGraph represents a powerful framework for building AI agents with robust decision-making capabilities. By mastering LangGraph, you will:</div><ul><li><strong>Design Flexible Workflows</strong>: Create intelligent systems that react and adapt to user input and evolving scenarios.</li><li><strong>Enable Autonomous Systems</strong>: Build systems capable of acting independently, managing success, failure, and conditions based on real-time data.</li><li><strong>Enhance Decision-making</strong>: Make data-driven decisions by integrating dynamic decision logic and understanding the flow of information between nodes, states, and edges.</li></ul><div><br /></div><div><strong>Who Should Register</strong><br /> This guided project is ideal for:</div><ul><li><strong>Developers</strong>: Those interested in building intelligent AI systems that require dynamic decision-making.</li><li><strong>AI Enthusiasts</strong>: Anyone looking to deepen their understanding of AI workflows and how to build flexible, autonomous systems.</li><li><strong>Software Engineers</strong>: Developers working on user authentication or similar workflows that require decision-based logic and state management.</li></ul><div><br /></div><div><strong>What You’ll Need</strong><br /> Before starting this project, ensure you have the following:</div><ul><li><strong>Basic Programming Knowledge</strong>: Familiarity with basic programming concepts will be helpful, especially in Python.</li><li><strong>Understanding of Decision-making</strong>: While prior experience with decision-making workflows is a plus, it’s not required.</li><li><strong>A Computer with a Modern Browser</strong>: Chrome, Edge, Firefox, or Safari to run and interact with the project tools.</li></ul><div><br /></div><div><strong>What You’ll Build</strong><br /> By the end of this guided project, you will have:</div><ul><li><strong>Mastered LangGraph</strong>: A deep understanding of how to build and connect the essential components of LangGraph for creating AI workflows.</li><li><strong>Built Dynamic Workflows</strong>: Created user authentication workflows that handle success and failure scenarios and adapt to changing conditions.</li><li><strong>Developed Autonomous Systems</strong>: Gained hands-on experience in designing systems that make real-time decisions based on data inputs and conditions.</li></ul><div><br /></div><div>Embark on this exciting journey with LangGraph to build intelligent AI agents that think, adapt, and make decisions in real-time. Elevate your AI development skills and start building dynamic decision-making systems today!</div>
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LangGraph 101: Learn to Build Agentic Workflows

Create agentic workflows with LangGraph by learning key components like nodes, states, edges, and conditional edges through a user authentication use case. Learn how to design AI workflows that adapt to real-time inputs and manage state-driven logic effectively. You’ll explore how to code success and failure scenarios, build dynamic decision-making systems, and create workflows tailored to diverse conditions. Perfect for developers and AI enthusiasts, this project focuses on equipping you with practical skills to design flexible, autonomous AI systems for real-world applications. 

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  <div><strong>Imagine having a data analyst at your fingertips</strong> who understands natural language and can perform complex analyses without requiring you to write a single line of code. What if you could simply ask questions about your data and receive immediate insights, visualizations, and even predictive models? This is the power of combining <strong>language models with specialized data science tools</strong>.</div><div><br />In this hands-on lab, you'll build a conversational AI system that makes data science accessible to everyone in your organization—from marketing specialists analyzing customer segments to executives exploring sales trends, all without technical barriers.<br /><br /></div><h1>Project Overview</h1><div>This lab teaches you to create an intelligent assistant that handles the entire data workflow through natural language requests:</div><div>1️⃣ <strong>Data Discovery &amp; Exploration</strong> - Automatically identify available datasets, summarize their structure, and provide quick statistics<br />2️⃣ <strong>Analysis &amp; Visualization</strong> - Transform requests like "Show the relationship between customer age and spending" into visualizations<br />3️⃣ <strong>Predictive Modeling</strong> - Train and evaluate machine learning models through conversation<br />4️⃣ <strong>Context Management</strong> - Maintain conversation history to enable follow-up questions and complex analyses</div><div><br />By connecting specialized LangChain tools through an agent executor, you'll create a seamless experience where users can move from raw data to actionable insights using only conversation.<br /><br /></div><h1>What You'll Learn</h1><div>By completing this lab, you will:</div><ul><li>Design effective <strong>tool-based agents</strong> that reason about when to use specific data functions</li><li>Build a collection of <strong>specialized tools</strong> for different data science tasks</li><li>Create <strong>multi-step workflows</strong> that maintain context across analyses</li><li>Implement <strong>natural language interfaces</strong> to technical data processes</li><li>Learn how to handle ambiguous user requests with <strong>clarification techniques</strong></li></ul><div><br /></div><h1><strong>Who Should Do This Lab</strong></h1><div>This project is ideal for:</div><ul><li><strong>Developers</strong> looking to build practical AI applications with immediate business value</li><li><strong>Data scientists</strong> wanting to make their expertise available to non-technical colleagues</li><li><strong>Technical leaders</strong> exploring how AI can democratize data-driven decision making</li><li><strong>AI enthusiasts</strong> interested in creating assistants that solve real-world problems</li></ul><div>No advanced ML expertise required—basic Python knowledge and curiosity about AI applications are all you need.<br /><br /></div><h1>What You Need</h1><div>✅ <strong>A browser</strong> to access the lab environment<br />✅ <strong>Basic Python knowledge</strong> (understanding functions and data structures)<br />✅ <strong>Familiarity with data concepts</strong> (CSV files, simple statistics, basic ML terms)</div><div><br />By the end of this project, you'll have built an AI assistant that transforms how people interact with data—enabling anyone to ask questions and receive insights without writing code.</div>
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Build a LangChain-based AI-powered Data Analysis Assistant

Learn LangChain tools and agents while developing a data science assistant to automate tasks from exploring CSVs to training ML models. This project guides you through creating a natural language interface that makes data analysis accessible to non-technical users.  Build specialized tools that handle everything from listing available datasets to generating statistics and evaluating machine learning models. Learn how AI agents interpret user requests, select appropriate tools, and execute complex data workflows through conversation. 

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  <div>As businesses are increasingly moving toward data-driven decision-making, the ability to derive meaningful insights from raw data is becoming all the more essential. The IBM Data Analyst Capstone Project gives you the opportunity to apply the skills and techniques learned throughout the IBM Data Analyst Professional Certificate. You will be working on a project simulating a real-life scenario with actual datasets. The project would involve carrying out tasks commonly performed by professional data analysts, such as data collection from multiple sources, data wrangling, exploratory analysis, statistical analysis, data visualization, and creating interactive dashboards.  <br /><br />Throughout the project, you will demonstrate your proficiency in tools such as Jupyter Notebooks, SQL, and Relational Databases Management System (RDBMS), and Business Intelligence (BI) tools like IBM Cognos Analytics. You will also apply Python libraries, including Pandas, Numpy, Scikit-learn, Scipy, Matplotlib, and Seaborn. <br /><br />Your final deliverable will be a comprehensive data analysis report that includes an executive summary, detailed insights, and a conclusion for organizational stakeholders. <br /><br />We recommend completing the previous courses in the Professional Certificate before starting this capstone project, as it integrates all key concepts and techniques into a single, real-world scenario. <br /><br /></div><h1>Course Learning Objectives</h1><ul><li>Apply techniques to gather and wrangle data from multiple sources. </li><li>Analyze data to identify patterns, trends, and insights through exploratory techniques. </li><li>Create visual representations of data using Python libraries to communicate findings effectively. </li><li>Construct interactive dashboards with BI tools to present and explore data dynamically. </li></ul><h1>Course Syllabus</h1><div><strong>Welcome to the Course</strong></div><ul><li>Video: Course Introduction</li><li>Reading: General Information: About the course</li><li>Reading: Course Learning Objectives and Course Syllabus</li><li>Video: Project Overview</li><li>Reading: Project Scenario</li><li>Reading: Grading Scheme</li></ul><div><strong>Module 1: Data Collection<br />Collecting Data Using APIs</strong></div><ul><li>Reading: Module 1 Introduction and Learning Objectives</li><li>(Optional) Lab 1: Review Of Accessing APIs</li><li>Reading: API Access Details </li><li>Lab 2:  Collecting Data Using APIs</li><li>Checklist: Collecting Data Using APIs</li></ul><div><strong>Collecting Data Using Webscraping</strong></div><ul><li>Lab 3: Review Of Web Scraping</li><li>Lab 4: Collecting Data Using Web Scraping</li><li>Checklist: Collecting Data Using Webscraping</li></ul><div><strong>Exploring Data</strong></div><ul><li>Reading: About the Dataset</li><li>Lab 5: Exploring the Dataset</li><li>Checklist:  Exploring Data</li><li>Graded Quiz: Data Collection</li></ul><div><strong>Module 2: Data Wrangling</strong></div><div><strong>Finding Duplicates</strong></div><ul><li>Reading: Module 2 Introduction and Learning Objectives</li><li>Reading: Assignment Overview</li><li>Lab 6: Finding Duplicates</li><li>Checklist: Finding Duplicates</li></ul><div><strong>Removing Duplicates</strong></div><ul><li>Lab 7: Removing Duplicates</li><li>Checklist: Removing Duplicates</li></ul><div><strong>Finding Missing Values</strong></div><ul><li>Lab 8: Finding Missing Values</li><li>Checklist: Finding Missing Values</li></ul><div><strong>Imputing Missing Values</strong></div><ul><li>Lab 9: Impute Missing Values</li><li>Checklist: Imputing Missing Values</li></ul><div><strong>Normalizing Data</strong></div><ul><li>Lab 10: Normalizing Data</li><li>Checklist: Normalizing Data</li></ul><div><strong>Assignment Overview</strong></div><ul><li>Lab 11: Data Wrangling</li><li>Checklist: Data Wrangling</li><li>Graded Quiz: Data Wrangling</li></ul><div><strong>Module 3: Exploratory Data Analysis</strong></div><div><strong>Assignment Overview</strong></div><ul><li>Reading: Module 2 Introduction and Learning Objectives</li><li>Reading: Assignment Overview</li><li>Lab 12: Exploratory Data Analysis</li><li>Checklist: Exploratory Data Analysis</li></ul><div><strong>Analyzing the data distribution</strong></div><ul><li>Lab 13: Finding How The Data Is Distributed</li><li>Checklist: Analyzing the data distribution</li></ul><div><strong>Handling Outliers</strong></div><ul><li>Lab 14: Finding Outliers</li><li>Checklist: Handling Outliers</li></ul><div><strong>Correlation</strong></div><ul><li>Lab 15: Finding Correlation</li><li>Checklist: Correlation</li><li>Graded Quiz: Exploratory Data Analysis</li></ul><div><strong>Module 4: Data Visualization</strong></div><div><strong>Assignment Overview</strong></div><ul><li>Reading: Module 4 Introduction and Learning Objectives</li><li>ReadIng: Assignment Overview</li><li>Lab 16: Data Visualization</li><li>Checklist: Data Visualization</li></ul><div><strong>Visualizing Distribution Of Data</strong></div><ul><li>Lab 17: Histograms</li><li>Lab 18: Box Plots</li><li>Checklist: Visualizing Distribution Of Data</li></ul><div><strong>Visualizing Relationship</strong></div><ul><li>Lab 19: Scatter Plot</li><li>Lab 20: Bubble Plots</li><li>Checklist: Visualizing Relationship</li></ul><div><strong>Visualizing Composition of Data</strong></div><ul><li>Lab 21: Pie Charts</li><li>Lab 22: Stacked Charts</li><li>Checklist: Visualizing Composition of Data</li></ul><div><strong>Visualizing Comparison of Data</strong></div><ul><li>Lab 23: Line Charts</li><li>Lab 24: Bar Charts</li><li>Checklist:  Visualizing Comparison of Data</li><li>Graded Quiz: Data Visualization</li></ul><div><strong>Module 5: Building A Dashboard</strong></div><div><strong>Assignment Overview</strong></div><ul><li>Reading: Module 5 Introduction and Learning Objectives</li><li>Reading: Assignment Overview</li></ul><div><strong>Dashboards</strong></div><ul><li>Lab 25: Option A - Building A Dashboard With IBM Cognos Analytics</li><li>Lab 26: Option B - Building A Dashboard With Google Looker Studio</li><li>Checklist: Dashboards</li><li>Graded Quiz: Building a Dashboard</li></ul><div><strong>Module 6: Final Assignment: Present Your Findings</strong></div><div><strong>How To Present Your Findings</strong></div><ul><li>Reading: Module 6 Introduction and Learning Objectives</li><li>Video: Elements Of A Successful Data Findings Report</li><li>Lab: Structure Of A Report</li><li>Video: Best Practices For Presenting Your Findings</li><li>(Optional)  Lab 27: Getting Started With PowerPoint For The Web</li><li>(Optional)  Lab 28: Basics of PowerPoint</li><li>(Optional) Lab 29: Save your PowerPoint Presentation as PDF</li></ul><div><strong>Final Presentation</strong></div><ul><li>Reading: Assignment Overview</li><li>Exercise: Preparing Your Presentation</li><li>Peer-graded Assignment</li></ul><div><strong>Course Wrap Up</strong></div><ul><li>Congratulations and Next Steps</li><li>Thanks from the Course Team</li><li>Copyrights and Trademark</li></ul><div><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>This course requires you to be proficient in data analysis and have experience using SQL, Relational Databases, performing data collection, data wrangling, data analysis, &amp; data visualization with Python libraries, and using a BI tool like IBM Cognos Analytics or Google Looker. I</div>
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IBM Data Analytics and Visualization Capstone Project

Showcase your data analysis skills to prospective employers by carrying out common tasks performed by data analysts on a data set simulating a real-life business scenario and creating a comprehensive data analysis report.  

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  <div>"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large data sets. Data visualization plays an essential role in the representation of both small and large scale data.</div><div>One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions.</div><div>The main goal of this course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using the open source language R. </div>
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Data visualization with R

Data visualization is the presentation of data with graphics. It's a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this course you will learn how to create beautiful graphics and charts, customizing the look and feel of them as you wish.

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  <div>​Selecting the appropriate AI model for your tasks can be challenging, especially when deciding between standard and reasoning modes. Anthropic's Claude 3.7 Sonnet offers a unique solution with its hybrid reasoning capabilities, allowing users to tailor the model's behavior to specific needs.<br /><br />By integrating Claude into your development environment, you can create a range of applications, including <strong>creative content generation, coding assistance, and analytical tasks</strong>. Claude's adaptability ensures that responses are both contextually appropriate and efficient, enhancing user engagement across various platforms.</div><div><br />Furthermore, Claude's "extended thinking" mode enables detailed, step-by-step reasoning, making it particularly effective for tasks requiring in-depth analysis. This feature enhances Claude's utility in solving complex problems and performing intricate tasks, providing users with a versatile and powerful AI tool.</div><div><br />By the end of this lab, you will have a solid understanding of how to effectively use Claude's API, design prompts that maximize AI performance, and choose between reasoning and non-reasoning models based on task requirements.</div><h1>A Look at the Project Ahead</h1><div>After completing this lab you will be able to:</div><ul><li>Learn how to set up and use Anthropic's Claude API. ​</li><li>Develop skills in prompt engineering to elicit high-quality outputs from AI models.</li><li>Understand the differences between Claude's reasoning capabilities and standard models, and learn to select the appropriate model based on specific task requirements. ​</li><li>Understand how to adjust Claude's "thinking budget" and other parameters to balance response quality and processing efficiency according to your application's needs.</li></ul><h1>What You'll Need</h1><div>To get started with this guided project, you should have:</div><ul><li>Access to modern web browsers like Chrome, Edge, Firefox, Internet Explorer, or Safari.</li></ul>
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Explore Reasoning v/s Non-Reasoning Models with Claude API

Use Anthropic's API to experiment with Claude Sonnet's reasoning and non-reasoning capabilities. By utilizing Anthropic's API, you can tailor Claude's behavior to align with your specific needs, whether it's for generating creative content, solving complex coding challenges, or engaging in detailed analytical tasks. This adaptability makes Claude a powerful tool for a wide range of applications, enhancing both productivity and the quality of AI-generated outputs. By experimenting with both models, we aim to identify key differences and determine which model is best suited for specific tasks.

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  <div>Imagine a world where patients can receive <strong>instant, AI-powered medical assistance</strong> anytime, anywhere. Whether it’s a late-night health concern, a follow-up on medication, or general health advice, <strong>AutoMed</strong> steps in as your intelligent virtual healthcare assistant. No more long waiting times, delayed responses, or unreliable online searches—AutoMed provides <strong>real-time, accurate, and personalized</strong> medical support tailored to each individual’s needs.</div><div><br />AutoMed is not just an ordinary chatbot—it’s a <strong>multi-agent AI system powered by AG2 (AutoGen)</strong>, designed to <strong>simulate expert medical consultation</strong> through intelligent collaboration. Instead of relying on a single AI model, <strong>AutoMed orchestrates multiple specialized agents</strong>, each dedicated to a specific task, ensuring <strong>comprehensive, accurate, and real-time</strong> medical guidance. With its <strong>adaptive intelligence and multi-agent communication</strong>, AutoMed delivers <strong>human-like, context-aware conversations</strong> that go beyond basic symptom checkers.<br /><br /><strong>Disclaimer</strong>: This guided project is designed to introduce learners to AG2 (AutoGen). The medical advice provided should not be considered a substitute for professional medical consultation, diagnosis, or treatment. Always seek guidance from a qualified healthcare professional.</div><h1>A Look at the Project Ahead</h1><div>After completing this lab you will be able to:</div><ul><li>Learn how <strong>AG2</strong> enables <strong>multi-agent AI systems</strong> for complex workflows.</li><li>Explore how <strong>AG2 integrates with LLMs</strong> like GPT-4 for dynamic AI-driven conversations.</li><li>Implement <strong>agent-to-agent communication</strong> for <strong>intelligent medical decision-making</strong>.</li><li>Develop <strong>multiple AI agents</strong> that interact and collaborate to handle different healthcare tasks.</li></ul><h1>What You'll Need</h1><div>The IBM Skills Network Labs environment comes with many things pre-installed (e.g. Docker) to save the  hassle of setting everything up. This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.</div>
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Build MultiAgent Chatbot with AG2 (AutoGen) for Healthcare

Learn to build AI agents using AG2 (AutoGen) multi-agent framework. In this project you will create AutoMed Multi LLM Agent for health treatment recommendations. It leverages Large Language Models (LLMs) to analyze user symptoms, suggest treatments, and access medical databases for accurate insights. You will build multiple AI agents that interact with each other, collaborate on complex medical queries, and automate healthcare assistance. These agents can coordinate tasks, fetch real-time medical data, and provide context-aware responses for better decision-making.

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  <div>Discover how generative AI can help you create engaging, personalized learning content and improve your productivity so you can enhance student outcomes. <br /><br /></div><div>During this course, you’ll explore gen AI methodologies and best practices for implementing AI in education. You’ll look at how it can be used to create content, enhance personalized learning, special education, and adaptive learning. You’ll get hands-on with popular gen AI tools, including IBM watsonx, ChatGPT, Claude, and Khanmigo in education. Plus, you’ll investigate the ethical implementation of gen AI, considering privacy protection, bias mitigation, and the creation of inclusive learning environments.   <br /><br /></div><div>Throughout, you’ll hear from industry experts, who share insights on the future of gen AI in education. You’ll build your gen AI expertise in hands-on labs and interactive activities. Plus, you’ll complete a final project where you’ll apply all that you’ve learned to a practical, real-world scenario.  <br /><br /></div><div>Whether you’re an educator looking to revolutionize your classroom practices or simply want to streamline ad<br />ministrative tasks, this course will give you the gen AI skills you need to excel. Enroll today! <br /><br /><strong>Prerequisites</strong> </div><div> </div><div>This course is designed for educators who already have an educational or teaching background and want to enhance their teaching capabilities using gen AI. You should have a fundamental understanding of gen AI and instructional design. The following courses in the <strong>Generative AI for Educators</strong> specialization can help you become familiar with gen AI basics and prompt engineering techniques: </div><div> </div><ul><li><a href="https://www.coursera.org/learn/generative-ai-introduction-and-applications?specialization=generative-ai-for-everyone">Course 1: Generative AI: Introduction and Applications</a> </li><li><a href="https://www.coursera.org/learn/generative-ai-prompt-engineering-for-everyone?specialization=generative-ai-for-everyone">Course 2: Generative AI: Prompt Engineering Basics</a> </li></ul><div> </div><div><strong>Objectives</strong> </div><div>After completing this course, you will be able to: </div><div> </div><ul><li>Identify appropriate gen AI tools for education, considering pedagogy, integration ease, and cost, to address specific teaching needs </li><li>Align the content with learners’ abilities, preferences, and engagement goals to create personalized learning content </li><li>Leverage gen AI tools to design lesson plans and assessments to encourage dynamic and interactive learning </li><li>Apply ethical AI practices by safeguarding data privacy, mitigating bias, and promoting an inclusive learning environment </li></ul><div> </div><div> </div><div><strong>Course Outline</strong> </div><div> </div><div>This course is divided into three modules. You can complete each module at your own pace, but it’s recommended to set a goal of completing at least one module per week.   </div><div> </div><div><strong>Module 1: Gen AI Tools and Personalized Learning </strong> <br /> </div><div>In this module, you will explore the landscape of educational gen AI tools and select them based on pedagogical needs, integration capabilities, and cost considerations. You will also learn to evaluate the effectiveness of AI tools for different teaching requirements and identify principles for AI-enhanced personalized learning and advanced content customization techniques. Finally, you will be able to leverage AI-powered tools for content creation and implement strategies for differentiating instruction using AI-powered resources.  </div><div> </div><div> </div><div> </div><div><strong>Module 2: AI Integration and Performance Assessment</strong> <br /> </div><div>This module introduces you to how to integrate AI tools seamlessly into teaching practices and leverage them for learners’ evaluation. You will gain insight into designing AI-enhanced lesson planning aligning them with learning objectives. Additionally, you will learn to create assessment strategies using gen AI tools to gauge learners’ mastery of concepts and analyze AI-generated performance data. Finally, you will be able to leverage AI-powered feedback mechanisms to provide timely, data-driven insights that support learners’ growth and continuous improvement.  </div><div> </div><div> <br /><strong>Module 3: Ethical Implementation and Applied Project</strong> </div><div> </div><div>This module helps address ethical considerations while implementing gen AI in education, recognize bias, and develop its mitigation strategies. You will also learn to design data privacy protection strategies for AI integration. </div><div> </div><div>This module includes storyline interactivity based on the ethical guidelines while implementing gen AI in education.  </div><div> </div><div>The module includes a final project based on the concepts covered in the course. In this module, you will attempt a graded quiz to test and reinforce your understanding of concepts. The module also includes a glossary to enhance comprehension of generative AI-related terms.   <br /> <br /> </div><div> </div><div><strong>Tools/Software</strong> </div><div>In this course, you will explore no-cost versions of various gen AI tools and platforms, including: </div><div> </div><ul><li>Microsoft’s Copilot </li><li>OpenAI’s ChatGPT – A versatile AI language model for creating lesson plans, answering learners’ queries, and personalized tutoring  </li><li>Anthropic Claude – An advanced conversational AI model for generating insightful educational content and assisting in curriculum design </li><li>Khanmigo Tools for Teachers – A suite of AI-powered tools designed to assist teachers in lesson planning, curriculum alignment, and classroom management </li><li>TeachFlow – A tool for streamlining teaching workflows, providing AI-driven assistance for lesson planning and classroom management </li><li>Synthesia – A tool for creating engaging animated videos  </li></ul><div> </div><div>These tools are accessible via modern web browsers such as Chrome, Firefox, and Edge. Learners are not required to install these tools on their devices. </div><div> </div><div><strong>Tips for Success</strong> </div><ul><li>Stay organized and keep track of teaching strategies and learning requirements </li><li>Consistently practice using the gen AI tools and technologies covered in the course </li><li>Experiment with the examples provided to enhance your understanding and application of AI in education </li></ul><div> </div><div>Congratulations on taking this step to elevate your teaching career with gen AI! Enjoy your learning journey. </div>
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Generative AI: Empowering Modern Education

This course is for education professionals, including teachers, professors, instructional designers, education administrators, EdTech professionals, corporate trainers, education policymakers, online course creators, and consultants who want to advance their careers by leveraging the power of generative AI.  

<div>Imagine you're applying for a mortgage to buy your dream home. After weeks of gathering documents and waiting anxiously, you receive a simple rejection letter with no explanation. You're left wondering: <strong>What went wrong? Was it your income, your down payment, or something in your credit history?</strong> Without clear reasons, you have no idea what to fix before trying again. This is where <strong>Explainable AI (XAI)</strong> makes a difference—transforming vague rejections into specific, actionable feedback that gives you a clear path forward.<br><br>As AI becomes increasingly embedded in critical decision-making processes across industries, the ability to understand why and how models reach specific conclusions is essential for building trust, ensuring fairness, and meeting regulatory requirements.<br><br>Here's a glimpse into the <strong>IBM's AI Explainability 360 (AIX360)</strong> decision framework you'll master in this learning path—helping you navigate which explainability techniques work best for different scenarios<br><br><figure data-trix-attachment="{&quot;contentType&quot;:&quot;image/png&quot;,&quot;filename&quot;:&quot;methods-choice.png&quot;,&quot;filesize&quot;:164704,&quot;height&quot;:1362,&quot;sgid&quot;:&quot;eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaEpJalJuYVdRNkx5OXdiM0owWVd4ekwwRmpkR2wyWlZOMGIzSmhaMlU2T2tKc2IySXZOemdfWlhod2FYSmxjMTlwYmdZNkJrVlUiLCJleHAiOm51bGwsInB1ciI6ImF0dGFjaGFibGUifX0=--c4a675b2462a5482e72c3ee025f577e1a73da307&quot;,&quot;url&quot;:&quot;https://latest-catalog.skillsnetwork.site/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBVdz09IiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--a99a9c540b33c9edec72f28d5d853169efc695ae/methods-choice.png&quot;,&quot;width&quot;:2048}" data-trix-content-type="image/png" data-trix-attributes="{&quot;presentation&quot;:&quot;gallery&quot;}" class="attachment attachment--preview attachment--png"><img src="https://latest-catalog.skillsnetwork.site/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBVdz09IiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--a99a9c540b33c9edec72f28d5d853169efc695ae/methods-choice.png" width="2048" height="1362"><figcaption class="attachment__caption"><span class="attachment__name">methods-choice.png</span> <span class="attachment__size">160.84 KB</span></figcaption></figure><br><br>The XAI methodology flowchart illustrates how to choose the right explainability approach based on your specific needs. Don't worry if you find this confusing at first—you'll understand these concepts step by step as you progress through the learning path. The framework starts with a fundamental decision: Do you need to understand the data or the model? Then it guides you through choosing between sample-based or feature-based explanations, local explanations (for individual predictions) or global explanations (for the entire model). The flowchart shows various techniques available in the AIX360 toolkit, including ProtoDash for prototype-based explanations, SHAP for feature importance, TED for user-friendly explanations, and BRCG for directly interpretable models.<br><br>By completing this learning path, you'll gain practical experience with diverse explainable AI techniques using <strong>IBM's AI Explainability 360 (AIX360) </strong>open-source toolkit. Through four guided projects across different domains, you'll develop skills to create AI systems that are not only accurate but also transparent and trustworthy—expertise that's increasingly valuable as organizations face growing demands for responsible AI from regulators, customers, and internal stakeholders.</div><div><br></div><ul><li><strong>Employee Retention Analysis</strong> - Identify factors influencing whether employees stay or leave</li><li><strong>Credit Approval Decisions</strong> - Create transparent explanations for financial decisions</li><li><strong>Housing Market Predictions </strong>- Build interpretable rule-based models for property valuations</li><li><strong>Student Performance Prediction</strong> - Generate representative profiles explaining academic outcomes</li></ul><div><br>This expertise is increasingly valuable as organizations face growing demands for responsible AI. Whether enhancing existing models or building new systems with explainability by design, this learning path provides the foundation to implement XAI effectively in your work.</div>

Master Explainable AI using AIX360

Learn practical techniques on how to make AI systems transparent, explainable, and trustworthy with IBM's AIX360 library. 

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  <div>This comprehensive course is designed for aspiring and current Product Owners aiming to deepen their understanding of Scrum practices and enhance their Agile expertise. It discusses the Product Owner's role, collaborating effectively with project sponsors, and creating key Scrum artifacts. Through hands-on activities, you will develop initial artifacts, such as user stories and product backlogs, while mastering the essential Agile ceremonies, including kickoffs and sprint planning.<br /><br /></div><div>The course then explores the ways Product Owners manage sprints, prioritize product backlogs, and resolve roadblocks. You will learn about the creation of Sprint goals and acceptance criteria, as well as how to ensure value delivery and stakeholder alignment. You’ll learn about Agile retrospectives and continuous improvement strategies. You’ll also explore the ways Product Owners use tools and methods to balance Agile principles with practical documentation, including innovations such as AI in product management.<br /><br /></div><div>This course includes hands-on projects that allow you to apply your learning to a real-world scenario. You will calculate performance metrics, complete a sprint retrospective, and present findings to stakeholders. </div><div>Additionally, you will be guided through building an Agile artifact portfolio, preparing for certification, and optimizing your job search strategies.</div><div><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Product Owner and Scrum: The Kickoff</strong>: </div><ul><li><strong>Welcome to the Course</strong></li><li> <strong>Product Owner Role Fundamentals</strong></li><li> <strong>Module Summary and Assessment</strong></li></ul><div><strong>Module 2: Delivering Value to the Customer</strong></div><ul><li>Managing Sprints</li><li>Overcoming Issues and Roadblocks</li><li>Module Summary and Assessment</li></ul><div><strong>Module 3: Continuous Improvement</strong></div><ul><li>MVP for AI Features</li><li>Managing continuous improvement across the Agile process</li><li>Module Summary and Assessment</li></ul><div><strong>Module 4: Final Project and Assessment</strong></div><ul><li>Final Project Submission</li><li>Final Graded Quiz</li><li>Course Wrap-Up</li></ul><div><strong>Module 5: Certifications, Portfolio Development, and Job Readiness</strong></div><ul><li>Product Owner Certifications</li><li>Your Personal Portfolio and Job Search Guidance</li></ul><h1><strong>Course Learning Objective</strong></h1><ul><li>Apply product owner skills learned from all courses in the Product Owner professional certificate</li><li>Analyze a series of Agile scenarios and create key scrum artifacts and deliverables</li><li>Demonstrate the product owner’s role in each of the Agile ceremonies by working through a simulated Scrum project</li><li>Identify the Product Owner’s role in communication and collaboration among all stakeholders throughout the simulated Scrum project</li><li>Create summary documentation for the Sprint Retrospective based on the scenarios provided</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>Prior knowledge of Product Owner skills, tools, communication, stakeholder management, Agile, Scrum, and IT fundamentals is essential.</div>
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Product Owner Capstone

This course provides an opportunity for you to apply the Product Owner knowledge and skills learned throughout all prior courses in the Product Owner Professional Certificate (PC) program. This course will reinforce your preparation for the Professional Scrum Product Owner (PSPO) or other Product Owner certifications.  We encourage you to complete all courses in this Professional Certificate series before beginning this final course. You will be provided with a real-world Agile project scenario and numerous hands-on activities to further develop your Product Owner skills and experience. 

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  <div><br />Course Introduction <br /><br /></div><div>Elevate your career prospects with this capstone project, designed to help you showcase job-ready business analysis skills in a real-world scenario. <br /><br /></div><div>This hands-on experience allows you to apply business analysis concepts and techniques through a fictitious case study, Enhancing Operational Efficiency in a Multi-Specialty<strong> </strong>Hospital<strong>. </strong>While working on this project, you’ll apply key business analysis<strong> </strong>skills<strong>, including requirements gathering</strong>, <strong>stakeholder analysis</strong>, <strong>project management</strong>, <strong>process modeling</strong>, and <strong>risk assessment</strong>. Additionally, you’ll use tools like <strong>Excel</strong> for <strong>data analysis</strong> and <strong>Cognos</strong> or <strong>Google Looker</strong> for creating impactful <strong>dashboards</strong>. </div><div> </div><div>This project offers an opportunity to design key artifacts integral to a business analysis project, including a <strong>Business Requirements Document (BRD)</strong>, <strong>Requirements Traceability Matrix (RTM)</strong>, <strong>Stakeholder Analysis and Engagement Plan</strong>, <strong>Process Model Diagram</strong>, <strong>Scope Management Plan</strong> and <strong>Risk Mitigation Plan</strong>. <br /><br /></div><div>To conclude the project, you'll design a professional PowerPoint presentation summarizing your findings, sharpening your analytical and presentation skills. <br /><br /></div><div>By completing this project, you’ll refine your critical thinking and problem-solving abilities and business analysis skills that stand on your resume. Be prepared to power up your business analysis career! <br /><br /></div><div> <br /><br /></div><div><br />Course Objectives  <br /><br /></div><ul><li>Gain practical, in-depth experience that builds confidence and readiness for entry-level roles in business analysis </li><li>Apply the concepts and skills acquired to execute a practical business analysis project </li><li>Showcase proficiency in core business analysis skills, including requirements gathering, stakeholder analysis, process modeling, and risk assessment,  </li><li>Demonstrate proficiency in using relevant business analysis tools and technologies, such as Excel and Lucidchart </li></ul><div> </div>
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Capstone Project: Applying Business Analysis Skills

This project offers an opportunity to design key artifacts integral to a business analysis project, including a Business Requirements Document (BRD), Requirements Traceability Matrix (RTM), Stakeholder Analysis and Engagement Plan, Process Model Diagram, Scope Management Plan and Risk Mitigation Plan. To conclude the project, you'll design a professional PowerPoint presentation summarizing your findings, sharpening your analytical and presentation skills. 

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  <div>This Object-Oriented Programming (OOP) course is designed to empower beginner and experienced software developers with the skills needed to build robust and scalable Java applications. It provides an in-depth exploration of OOP principles, including encapsulation, inheritance, polymorphism, and abstraction, enabling you to create modular and maintainable code.<br /><br /></div><div>You will gain hands-on experience designing classes, implementing constructors, and mastering advanced OOP concepts such as interfaces, abstract classes, and method overloading. The course also covers collections, including lists, sets, queues, and maps, ensuring efficient data management in complex applications.<br /><br /></div><div>Additionally, you will learn essential file-handling techniques, work with dates and times, and integrate external services to enhance application functionality. Throughout the course, best practices in software design, such as modularity, code readability, and exception handling, are emphasized, preparing you for real-world software development challenges.</div><div>This course is part of the Java Development from IBM Professional Certificate, a structured learning path designed to provide practical programming experience. It is an ideal starting point for aspiring Java developers.<br /><br /></div><h1>Course Syllabus</h1><div><strong>Module 1: Object-Oriented Programming in Java</strong></div><ul><li>Learn core OOP principles: classes, objects, encapsulation, constructors</li><li>Explore inheritance, polymorphism, interfaces, abstract classes</li><li>Hands-on labs to apply OOP concepts in Java</li></ul><div><strong>Module 2: Advanced Object-Oriented Programming Concepts</strong></div><ul><li>Delve into inheritance, polymorphism, interfaces, inner classes</li><li>Apply concepts through real-world examples and practical labs</li></ul><div><strong>Module 3: The Java Collections Framework</strong></div><ul><li>Study lists, sets, queues, and maps for data management</li><li>Hands-on practice selecting the right collection type for different challenges</li></ul><div><strong>Module 4: File Management</strong></div><ul><li>Learn file handling: creating, reading, writing files, managing directories</li><li>Hands-on with file streams for input/output operations</li></ul><div><strong>Module 5: Handling Dates and Times and Service Integration</strong></div><ul><li>Work with Java’s date and time classes, including time zones and date calculations</li><li>Master time-based functionality for real-world applications</li></ul><div><strong>Module 6: Final Project and Course Summary</strong></div><ul><li>Apply concepts learned in a final project</li><li>Course review and consolidation of Java programming skills</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>Let your learners know what technology and skills they'll need prior to starting this guided project. Remember that the IBM Skills Network Labs environment comes with many things pre-installed (e.g. Docker) to save them the hassle of setting everything up. Also note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.<br /><br /></div><h1><strong>Course objectives</strong></h1><div>After completing this course, you will be able to:</div><ul><li>Apply Object-Oriented Programming (OOP) concepts</li><li>Define and implement classes and objects, demonstrating encapsulation and abstraction</li><li>Use advanced OOP concepts such as inheritance, polymorphism, interfaces, and method overloading</li><li>Employ the Java collections framework to manage data using lists, sets, queues, and maps</li><li>Read and write to files using Java streams</li><li>Handle directories effectively</li><li>Work with Java date and time classes for effective date manipulation and formatting</li><li>Integrate external services and call external APIs</li><li>Demonstrate your knowledge with the completion of a comprehensive Java programming project</li></ul><h1><strong>Prerequisites and Hardware Requirements</strong></h1><div>This course is recommended for budding and experienced software developers who want to understand object-oriented programming (OOP) in Java. To access the course materials, you will need a laptop or desktop with internet access.</div>
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Object Oriented Programming in Java

Java developers with object-oriented programming skills in the United States earn an average annual salary of approximately USD 91,024 (Indeed.com).In this course, you’ll gain hands-on experience with key OOP concepts such as encapsulation, abstraction, inheritance, and polymorphism. Learn to define and implement classes and objects. You’ll explore advanced techniques, including interfaces, method overloading, and the Java collections framework, managing data with lists, sets, queues, and maps, and handling file input/output operations.

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  <div>Over 90% of Fortune 500 companies use Java (Netguru) and entry-level Java developers can earn USD100,000+ per year with outstanding opportunities for swift salary growth. This course gives you the job-ready, fundamental skills to develop Java applications employers are looking for, and enables you to add this powerful, versatile language to your resume in just 4-5 weeks!  </div><div>During the course, you’ll learn to set up the Java environment and install and configure the Java Development Kit (JDK), Java Runtime Environment (JRE), and an Integrated Development Environment (IDE). You’ll explore key Java concepts, such as data types, variables, operators, and control flow statements. Plus, you’ll discover how arrays, strings, methods, and effective exception handling are used to create efficient programs.  <br /><br />Throughout, you’ll engage in hands-on exercises and, at the end, you’ll complete a final project covering a real-world scenario that reinforces your practical understanding.  <br /><br />If you’re keen to add Java to your resume and have job-ready experience you can talk about in interviews, enroll today and power up new career opportunities in just one month!<br /><br /></div><h1>Course Syllabus</h1><div><strong>Module 1:</strong> Introduction to the Java Environment and Ecosystem</div><div><strong>Module 2:</strong> Basic Programming Constructs in Java</div><div><strong>Module 3:</strong> Control Structures and String Handling</div><div><strong>Module 4:</strong> Robust Exception Handling</div><div><strong>Module 5:</strong> Final Project and Course Wrap-Up</div><div><br /></div><h1>Learning Objectives</h1><ul><li>Set up the Java environment</li><li>Install and configure the Java Development Kit (JDK), Java Runtime Environment (JRE), and Integrated Development Environment (IDE)</li><li>Describe the Java ecosystem and its applications across web, desktop, embedded, and mobile platforms</li><li>Explain Java fundamental coding concepts</li><li>Identify and utilize various programming constructs, including data types, variables, operators, and control flow statements</li><li>Work with arrays, strings, and methods to create efficient Java programs</li><li>Handle exceptions and manage data structures</li><li>Implement exception-handling techniques using try-catch blocks</li><li>Discuss the differences between checked and runtime exceptions</li><li>Synthesize knowledge gained throughout the course to complete a comprehensive project</li><li>Prepare for technical interviews through practice questions related to Java programming</li></ul><h1>Recommended Skills Prior to Taking this Course</h1><div>This course is recommended for budding and experienced software developers who want to understand Java programming.  If you are new to software development, <a href="https://www.coursera.org/learn/introduction-to-software-engineering?">Introduction to Software Engineering </a>is a recommended prerequisite. You will need a laptop or desktop with internet access to access the course materials.   </div>
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Java Programming for Beginners

This course is designed to equip beginner and experienced software developers and programmers with the essential skills to write and understand Java programs. It comprehensively explores fundamental programming concepts such as variables, data types, and control structures.You will gain hands-on experience writing functions and methods, understanding class structures, and implementing encapsulation, inheritance, and polymorphism. The course also delves into core technical practices and exception handling, enabling you to write efficient and error-free code.

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  <div>The global recommendation engine market is predicted to grow 37% annually through 2030 (Straits Times). The expertise to predict user preferences and drive engagement using AI recommendation system skills has become an essential business need and a highly sought-after skill using vector databases. </div><div>In this IBM mini-course, you’ll create two shareable projects that demonstrate your proficiency and readiness to develop AI-powered recommendation systems.  <br /> <br />You’ll get step-by-step instructions to create a real-life inspired food ordering recommendation system using Chroma DB and Hugging Face models. For your final project, you’ll use Chroma DB or your choice of PostgreSQL, Cassandra, or MongoDB to create a real-life job search recommendation system. This will demonstrate your ability to generate embeddings and implement similarity searches using Hugging Face natural language processing (NLP) algorithms. <br /> <br />Ready to start? Bring your vector, NoSQL, or relational database vector search skills to this course. If you don't already have these skills, you can attain these skills in other Vector Databases Fundamentals Specialization courses.  <br /> <br />Enroll today in this mini-course to advance your AI career!</div><h1>Course Syllabus</h1><ul><li>Welcome</li><li>Introduction to Hugging Face</li><li>Practice project</li><li>Final project</li></ul><h1>Learning Objectives</h1><ul><li>Develop a recommendation system using the ChromaDB vector database and Hugging Face tools </li><li>Generate vector embeddings using natural language processing algorithms</li><li>Perform similarity searches using vector embeddings </li><li>Search a database using a PDF as the input query</li></ul><div><br /></div><h1>Recommended Skills Prior to Taking this Course</h1><div>This course is the culminating project course in the series linked above. We highly recommend that you take the previous courses before this one.</div><div>To get the most out of this course, you should be comfortable with the following:</div><div>Technologies:</div><ul><li>JavaScript</li><li>ChromaDB</li><li>Git and GitHub</li></ul><div>Concepts:</div><ul><li>Vector embeddings</li><li>Natural language processing concepts</li><li>Recommendation systems</li><li>Similarity searches</li></ul><div>If you take the previous courses in the series, you will learn what you need for success in this course.</div>
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Vector Database Projects: AI Recommendation Systems

In this course, you will apply your knowledge of vector databases, natural language processing, embeddings, and similarity searches to create database-backed recommendation systems in a practice project and a final capstone project using JavaScript and ChromaDB.This course is the last in a series of microcourses. Follow the link below to read about the series and see how this program can benefit you and advance your career.

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  <div>In this course, you will learn how to design, deploy, load, manage, and query data warehouses and data marts. You will begin by understanding different analytics repositories including data marts, data warehouses, data lakes, data lakehouses and their functions and uses. They are designed to enable rapid business decision-making through accurate and flexible reporting and data analysis. <br /> </div><div>A data warehouse is one of the most fundamental business intelligence tools in use today, and one that successful Data Engineers must understand. Additionally, you will learn to design, model, and implement data warehouses and explore data warehousing architectures such as Star and Snowflake schemas. Finally, you will learn how to populate data warehouses using Extract, Transform, and Load (ETL) and Extract, Load, Transform (ELT) processes, verify data, query data, and use Cubes, Rollups, and materialized views/tables.  <br /><br /></div><div>The hands-on labs in this course will enable you to apply what you learn and gain a practical knowledge of data warehousing. You will work with repositories such as PostgreSQL and IBM Db2.</div><div><br /></div><h1>Course Syllabus</h1><ul><li>Module 1: Data Warehouses, Data Marts, and Data Lakes</li><li>Module 2: Designing, Modeling, and Implementing Data Warehouses</li><li>Module 3: Final Assignment and Final Quiz</li><li>Module 4 (Optional): IBM Db2</li></ul><div><br /></div><h1>What you'll learn</h1><ul><li>Discuss the fundamentals of data warehouses, data marts, and data lakes by analyzing their features and advantages.</li><li>Examine organizations' decision-making processes to select specific data warehouse systems and vendors.    </li><li>Design and populate a data warehouse, and model and query data using Cubes, Rollups, and materialized views.</li><li>Design and load data into a data warehouse, write aggregation queries, create materialized query tables, and create an analytics dashboard.</li></ul><h1><strong>Prerequisites</strong></h1><div>To succeed in this course, it is recommended that you should have a fundamental knowledge of Relational Database Management Systems (RDBMS) and a working knowledge of Structured Query Language (SQL).</div><div><br /></div>
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Data Warehouse Fundamentals

This course introduces you to designing, implementing and populating a data warehouse and analyzing its data using SQL & Business Intelligence (BI) tools. This course also covers data repositories including data marts, data lakes, data reservoirs, and Cognos Analytics for visualization. 

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  <div>This course is designed for everyone, including professionals, executives, students, and enthusiasts, interested in learning about generative AI and leveraging its capabilities in their work and lives.   <br /><br /></div><div>This course is your first step toward understanding the capabilities of generative AI, powered by different models, including large language models (LLMs).   <br /><br />In this course, you will learn about the fundamentals and evolution of generative AI. You will explore the capabilities of generative AI in different domains, including text, image, audio, video, virtual worlds, code, and data. You will understand the applications of generative AI across different sectors and industries. You will learn about the capabilities and features of common generative AI models and tools, such as GPT, DALL-E, Stable Diffusion, and Synthesia.    <br /><br />Hands-on labs, included in the course, provide an opportunity to explore the use cases of generative AI through IBM Generative AI Classroom and popular tools like ChatGPT. You will also hear from the practitioners about the capabilities, applications, and tools of generative AI.</div>
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Introduction to Generative AI

Dive into the new and exciting world of Generative AI and Large Language Models (LLM). Understand the capabilities of generative AI and its use cases in the real world. Identify the applications of generative AI in different sectors and industries. Explore common generative AI models and tools for text, code, image, audio, and video generation.

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  <div>This course is designed for everyone, including professionals, executives, students, and enthusiasts interested in leveraging effective prompt engineering techniques to unlock the full potential of generative artificial intelligence (AI) tools like ChatGPT and other LLMs. <br /><br /></div><div>Prompt engineering is a process to effectively guide generative AI models and control their output to produce desired results. In this course, you will learn the techniques, approaches, and best practices for writing effective prompts. <br /><br />You will learn about prompt techniques like zero-shot and few-shot, which can improve the reliability and quality of large language models (LLMs). You will also explore various prompt engineering approaches like Interview Pattern, Chain-of-Thought, and Tree-of-Thought, which aim at generating precise and relevant responses. <br /><br />You will be introduced to commonly used prompt engineering tools like IBM watsonx Prompt Lab, Spellbook, and Dust.  <br /><br />The hands-on labs included in the course offer an opportunity to optimize results by creating effective prompts in the IBM Skills Network AI Classroom. You will also hear from practitioners about the tools and approaches used in prompt engineering and the art of writing effective prompts.<br /><br /></div>
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Introduction to Prompt Engineering

Learn how to improve the effectiveness of your AI by using the latest prompt engineering techniques. Apply best practices for creating prompts and explore examples of impactful prompts. Practice common prompt engineering techniques and approaches for writing effective prompts for different LLMs.

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