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Building Generative AI-Powered Applications with Python

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IntermediateCourse

This course provides an opportunity to work on guided projects that provide step-by-step instructions to build generative AI-powered applications. You'll utilize Python, along with related libraries like Flask and Gradio, and frameworks such as Langchain.

4.7 (172 Reviews)

Language

  • English

Topic

  • Artificial Intelligence

Industries

  • Information Technology

Enrollment Count

  • 20.55K

Skills You Will Learn

  • Data Science, Machine Learning, Computer Science, Software Development

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 7 Weeks

Platform

  • Coursera

Last Update

  • June 16, 2025
About this Course
Ready for an interactive learning experience to develop applications and chatbots for diverse use cases using generative AI? 

This course provides an opportunity to work on guided projects that provide step-by-step instructions to build generative AI-powered applications. You'll utilize Python, along with related libraries like Flask and Gradio, and frameworks such as Langchain.

In the course, you will work on hands-on projects to build chatbots and apps by utilizing popular large language models (LLMs) such as GPT-3 and Llama 2, hosted on platforms such as IBM watsonx and Hugging Face. Additionally, you'll explore retrieval-augmented generation (RAG) technology, enhancing LLMs by incorporating external information beyond their training data. This course also equips you to build voice-enabled chatbots and apps using IBM Watson® Speech Libraries for Embed.

To develop these projects, you'll be using Python, making it essential to have a basic understanding of the language. While knowing some HTML, CSS, and JavaScript can be beneficial, it's not a requirement. The course includes supporting videos and readings to build a foundational understanding of models, frameworks, and technologies used in the projects.

Course Syllabus

Module 1: Image Captioning with Generative AI
  • Welcome to the Course
  • Captioning Photos with Generative AI
  • Module Summary and Assessment
Module 2: Create Your Own ChatGPT-like Website
  • Create Chatbot with Open Source LLMs
  • Module Summary and Assessment
Module 3: Create a Voice Assistant
  • Create a Voice Assistant with GPT-3 and IBM Watson
  • Module Summary and Assessment
Module 4: Generative AI-Powered Meeting Assistant
  • Create an App for Summarizing Meetings
  • Module Summary and Assessment
Module 5: Summarize Your Private Data with Generative AI
  • Create an App for Summarizing Your Private Data
  • Module Summary and Assessment
Module 6: Babel Fish with LLM and STT TTS
  • Create a Translation Assistant
  • Module Summary and Assessment
Module 7: Build an AI Career Coach
  • Create a Personalized Job Application Coach
  • Module Summary and Assessment
  • Course Wrap up

Recommended Skills Prior to Taking this Course

This course is suitable for individuals with a fundamental knowledge of generative AI, Python programming, and an interest in developing apps and chatbots. 
To learn about the fundamentals of generative AI, please consider the following course:
To learn about development with Python programming, please consider the following course:
In addition, it can be beneficial, but not mandatory, if you have a basic knowledge about HTML, CSS, and JavaScript.  You may take the following course for a basic understanding:

Course Learning Objectives

  • Explain the core concepts of generative AI models, AI technologies, and AI platforms such as IBM watsonx and Hugging Face.  
  • Integrate and enhance large language models (LLMs) using RAG technology to infuse intelligence into apps and chatbots. 
  • Utilize Python libraries like Flask and Gradio to create web applications that interact with generative AI models. 
  • Build generative AI-powered applications and chatbots using generative AI models, Python, and related frameworks.

Instructors

Sina Nazeri

Data Scientist at IBM

I am grateful to have had the opportunity to work as a Research Associate, Ph.D., and IBM Data Scientist. Through my work, I have gained experience in unraveling complex data structures to extract insights and provide valuable guidance.

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Raghul Ramesh

SME

Artificial Intelligence , Big Data , Cloud Architect, Have more than 17 years of experience in working with banking, finance, retail, ecommerce, pharma, ecommerce domain projects,

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Contributors

Kang Wang

Data Scientist

I was a Data Scientist in the IBM. I also hold a PhD from the University of Waterloo.

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