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IntermediateGuided Project

Think LLMs are over-hyped and not practical for real-world problems? Discover how Generative AI can solve real challenges using LangGraph. Move beyond basic chatbots, adding real value to our fictional company. Learn to integrate LLMs into Typescript and Python applications, implement image processing, set up cron jobs for dynamic system updates, and apply AI-driven insights for dynamic pricing. You’ll also explore Human-In-The-Loop(HITL) systems. This project equips you with the skills and techniques to harness the true potential of LLMs and make a tangible impact in real-world applications.

4.4 (24 Reviews)

Language

  • English

Topic

  • Artificial Intelligence

Enrollment Count

  • 109

Skills You Will Learn

  • Artificial Intelligence, Generative AI, LangChain, LangGraph

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 2.5 hours

Platform

  • SkillsNetwork

Last Update

  • October 15, 2025
About this Guided Project
I've interacted with many people skeptical about the practical value of Large Language Models (LLMs) and Generative AI—thinking they’re just over-hyped tools limited to chatbots or PDF summarizers. Perhaps you’ve tried building your own chatbot or Retrieval-Augmented Generation (RAG) system and questioned if AI truly delivers real-world benefits. You’re not alone.

In this Guided Project, we’ll dispel those doubts by demonstrating how Generative AI can solve genuine problems and add tangible value to businesses. Through hands-on examples, we’ll enhance our fictional company, Tech Cafe, by integrating advanced AI features into their operations. You’ll learn to move beyond basic chatbots and harness the true potential of LLMs using LangGraph.

A Look at the Project Ahead

By completing this project, you will:
  • Integrate a Large Language Model (LLM) into a Node.js application
    Learn how to seamlessly incorporate LLMs like Llama 3 and Granite models provided by watsonx.ai into your applications.
  • Implement multiple LangGraph-based workflows for complex and modular code flows
    Understand how to structure AI-driven workflows using LangGraph to create flexible and maintainable code.
  • Implement image processing using a Large Language Model (LLM)
    Use LLMs to analyze images for real-time data, such as counting foot traffic to adjust cafe operations.
  • Set up a cron job to periodically update system state
    Automate tasks to keep your application responsive to changing data and conditions.
  • Implement dynamic pricing based on AI-driven insights
    Adjust prices in real-time using AI insights to maximize profitability and efficiency.
  • Implement Human-In-The-Loop (HITL)
    Incorporate human oversight into your AI workflows to improve accuracy and trustworthiness.

Why This Project Matters

LLMs and Generative AI are transforming industries by automating complex tasks and providing insights that were previously unattainable. However, many perceive these technologies as over-hyped due to a lack of practical examples demonstrating their real-world applicability. This project bridges that gap by showcasing how AI can be leveraged to solve actual business challenges, moving beyond theoretical concepts to practical implementation.

By working through this project, you’ll gain hands-on experience with:

 • LangGraph: A powerful library for creating flexible AI workflows.
 • LLMs in Real-world Applications: Applying models like Llama 3 in practical scenarios.
 • AI-Driven Decision Making: Using AI to make informed business decisions, such as dynamic pricing.
 • Modular and Scalable Code Design: Structuring your code to adapt to future changes and requirements.

What You’ll Need

To successfully complete this project, you should have:
  • Basic knowledge of JavaScript or Python and Node.js
    Familiarity with Node.js OR Python will help you navigate and modify the application code.
    • You can choose between the Typescript version or the Python version of the project, depending on your preference.
  • A Modern Web Browser
    The platform works best with current versions of Chrome, Edge, Firefox, or Safari.

Get Started with AI-Powered Solutions

Join us in this Guided Project to unlock the true potential of Generative AI and LLMs. By the end of this journey, you’ll have the skills and confidence to implement AI-driven solutions that solve real-world problems and add significant value to any business.

Embark on this hands-on project today and transform your skepticism into expertise. Let’s prove that LLMs are not just hype—they’re powerful tools that can solve real problems and drive innovation.

Instructors

Bradley Steinfeld

Lover of technology and learning

I work for IBM. I like all tech, especially AI!

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Faranak Heidari

Data Scientist at IBM

Detail-oriented data scientist and engineer, with a strong background in GenAI, applied machine learning and data analytics. Experienced in managing complex data to establish business insights and foster data-driven decision-making in complex settings such as healthcare. I implemented LLM, time-series forecasting models and scalable ML pipelines. Enthusiastic about leveraging my skills and passion for technology to drive innovative machine learning solutions in challenging contexts, I enjoy collaborating with multidisciplinary teams to integrate AI into their workflows and sharing my knowledge.

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