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LangGraph: From Basics to Advanced AI Agents with LLMs
Highest Rated
Rating: 4.5 out of 5(47 ratings)
969 students

LangGraph: From Basics to Advanced AI Agents with LLMs

Learn how to build custom AI Agents with LangGraph
Created byTensor Teach
Last updated 5/2025
English

What you'll learn

  • Software Engineers looking to build Generative AI applications with LangGraph.
  • Data Scientists looking to build Generative AI applications with LangGraph.
  • Learners looking to further their knowledge beyond LangChain.
  • Generative AI enthusiasts looking to learn the latest methods for building AI agents.

Course content

3 sections19 lectures1h 38m total length
  • What Is LangGraph?3:27
  • Drafting Our First Agent5:11
  • Creating The Agents State4:50

    Translate the flow into a graph state by defining a typed dict with input, assigned node, and prev node to write, then propagate the state through manager and worker nodes.

  • Building Our Nodes5:09
  • Note on Conditional Edges & Routing Functions0:18
  • Building Our Edges6:37
  • Compiling Our Graph & Testing It9:09
  • Section Notebook - LangGraph Core Concepts0:03

Requirements

  • Some python programming experience
  • Previous experience with LangChain

Description

Embark on a comprehensive journey into the world of AI agents with LangGraph. This course is designed to guide you from fundamental concepts to advanced techniques, equipping you with the skills to build sophisticated AI systems. Starting with the core principles, you'll learn about graphs, nodes, edges, and states, and see how they form the foundation of LangGraph workflows. The course begins with constructing a basic agent, allowing you to grasp the essentials through hands-on practice.


Next, you'll dive deeper by building a News Writer Agent, enhancing your understanding by integrating state and tools into your agents. The focus will be on practical applications, ensuring you can visualize and test your agents effectively. Finally, the course introduces advanced techniques, including reflection, human-in-the-loop processes, checkpointers, and threads. You'll also learn to incorporate custom tools, adding versatility and functionality to your agents. Whether you're a beginner or looking to advance your skills, this course provides a structured, step-by-step approach to mastering AI agent development with LangGraph.


The goal of this course is to equip you with the understanding and skills you need to build your own agents. There are plenty of off-the-shelf agents available via LangGraph and other resources. However, in our experience, when building agents for production you will need to be able to customize. At the end of this course, it is our goal to make sure that you are capable of building your own custom workflows in LangGraph.


Note: Prior python programming experience and some experience with LangChain are required for this course.

Who this course is for:

  • Developers, Data Scientists, AI Engineers, and Enthusiasts looking to learn how to build AI Agents in LangGraph