LangGraph for Developers: From Zero to Hero

About this course

Master LangGraph, Agentic AI, Stateful Workflows & Production-Ready AI Systems

In this comprehensive LangGraph course, you will learn how to design, build, and deploy production-ready Agentic AI systems using LangGraph, Large Language Models (LLMs), MCP, and FastAPI.This course is built specifically for developers who want to master graph-based LLM orchestration and move beyond simple chatbot demos.

What You’ll Learn

By the end of this course, you will be able to:

• Build stateful AI agents using LangGraph
• Design graph-based LLM workflows with nodes, edges, and reducers
• Work with OpenAI and other LLM providers
• Implement control flow and conditional routing
• Add memory, persistence, and interrupt handling
• Use streaming and tool-calling capabilities
• Design Agentic AI architectures
• Implement Model Context Protocol (MCP)Build MCP-enabled tool discovery systems
• Develop and deploy AI Agent APIs using FastAPICore Topics CoveredLangGraph Fundamentals

State, Nodes, Edges & Reducers

Control Flow & Conditional Execution

Tool Calling & Streaming

Persistence & Time Travel Debugging

Memory & Sub-GraphsAgentic Design PatternsLangChain vs LangGraph Architecture

Model Context Protocol (MCP)MCP Server Integration

Production API DevelopmentFastAPI Integration

If you want to become an Agentic AI Developer and build real-world, production-ready AI systems using LangGraph, this course will take you from beginner to advanced, step by step.

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