LangGraph- Develop LLM powered AI agents with LangGraph

About this course

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

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

Agent patterns (≈ 4h, shared with the LangChain course): Reflection, Reflexion, Agentic RAG (Corrective/Self/Adaptive), ReAct with ToolNodeLangGraph-only (≈ 2h50m): persistence & interrupts, async execution, Studio & LangSmith Deployment, GPT-Researcher, CopilotKit

The topics covered in this course include:

LangChainLCELLangGraphAgentsMulti AgentsReflection AgentsReflexion AgentsLangSmithCrewAI VS LangGraphAdvanced RAGCorrective RAGSelf RAgAdaptive RAGGPT ResearcherLangGraph Ecosystem:

• LangGraph Studio / LangGraph IDELangGraph 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.

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