LangGraph- Develop LLM powered AI agents with LangGraph

Welcome to first LangGraph Udemy course !
This comprehensive course is designed to teach you how to QUICKLY harness the power the LangGraph library for LLM agentic applications.
This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM Agents solutions for a diverse range of topics.

Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python & LangChain. I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts .

Course map

1. Concepts (≈ 42m): what LangGraph is, graphs, flow engineering, core components

2. Agent patterns (≈ 4h, shared with the LangChain course): Reflection, Reflexion, Agentic RAG (Corrective/Self/Adaptive), ReAct with ToolNode

3. LangGraph-only (≈ 2h50m): persistence & interrupts, async execution, Studio & LangSmith Deployment, GPT-Researcher, CopilotKit

The topics covered in this course include:

• LangChain

• LCEL

• LangGraph

• Agents

• Multi Agents

• Reflection Agents

• Reflexion Agents

• LangSmith

• CrewAI VS LangGraph

• Advanced RAG

• Corrective RAG

• Self RAg

• Adaptive RAG

• GPT Researcher

• LangGraph Ecosystem:

  • LangGraph Studio / LangGraph IDE

  • LangGraph Cloud API

  • LangGraph Cloud Managed Service

    
    

Throughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LangGraph to create powerful, efficient, and versatile LLM applications for a wide array of usages.


This is not just a course, it's  also  a community. Along with lifetime access to the course, you'll get:

1. Dedicated troubleshooting support with me

2. Github links with additional AI resources, FAQ, troubleshooting guides

3. No extra cost for continuous updates and improvements to the course

Who this course is for

• AI Engineers, Software, backend and full-stack engineers who know LangChain and want stateful agents with LangGraph

• LangChain-course graduates who want the LangGraph-only sections (6–10) — see the overlap note

This course is not for you if:

• You're new to Python or LangChain

• You want a source-level tour of LangGraph's internals and abstract classes

• You want a concept-first, lecture-heavy course