LangGraph

About this course

LangGraph is one of the most powerful frameworks for building intelligent AI agents and workflow-driven applications. This course is designed to help you learn LangGraph from the ground up and apply it to real-world AI projects.

You will start by understanding the foundations of AI agents and LangChain before moving into LangGraph's graph-based architecture. Through hands-on examples, you will learn how to create stateful workflows using nodes, edges, conditional routing, memory, and checkpoints. As the course progresses, you will integrate Large Language Models (LLMs), external tools, databases, web search, and Retrieval-Augmented Generation (RAG) systems into your applications.

The course covers both fundamental and advanced topics, including conversational memory, Agentic RAG, Corrective RAG, reflection-based agents, Human-in-the-Loop workflows, SQL agents, and multi-tool AI systems. You will also learn how to monitor, trace, debug, and optimize AI workflows using LangSmith.

Every concept is explained step by step with practical coding demonstrations and real-world use cases. By the end of the course, you will be able to design, build, and deploy sophisticated AI agents that can reason, use tools, manage memory, and automate complex tasks.

Whether you are a developer, data scientist, AI enthusiast, or student, this course will provide the skills needed to build next-generation AI applications using LangGraph.

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