If you’re building conversational AI and tired of messy logic or hard-to-scale workflows, LangGraph makes it easier. It uses graphs to manage dialogue flow, so your bots stay organized even as they get more complex. Great for anything from support agents to multi-step AI tools.
We just published a full video course on the freeCodeCamp.org YouTube channel about LangGraph. It is a Python framework for building advanced conversational AI workflows. If you’re looking to build chatbots or AI agents that can handle more than just basic Q&A, this course is for you.
Your instructor, Vaibhav Mehra, walks you through everything step by step. You’ll learn how to use a graph-based structure to manage complex dialogue systems. This approach makes it easier to build scalable, flexible conversational applications powered by large language models.
Here’s a quick breakdown of what’s covered:
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The Basics: Get started with LangGraph, type annotations, and core elements.
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Agents: Build five different agents from scratch. Each one includes a walkthrough and coding exercises so you can follow along and try it yourself.
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AI Agents: Go deeper with AI-powered agents. These modules cover key design patterns and show you how to build more intelligent, adaptive systems.
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RAG (Retrieval-Augmented Generation): Learn how to integrate RAG into your LangGraph workflows for smarter, context-aware responses.
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Wrap-up: Recap what you’ve learned and see how all the pieces come together.
This is a hands-on course, so expect to write a lot of code and build real working examples. Whether you’re new to LangGraph or just want to sharpen your skills, this course will help you go from zero to production-ready applications.
Watch it now on the freeCodeCamp.org YouTube channel (3-hour watch).
Source: freeCodeCamp Programming Tutorials: Python, JavaScript, Git & MoreÂ
