
LangGraph Complete Course For Beginners (From ZERO To HERO)
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Vaibhav Mehra's video course introduces LangGraph, a Python library for graph-based conversational systems. It begins with the type annotations the library relies on, then builds up a series of agents, each adding a new idea, before moving to retrieval-augmented generation.
The first agents are simple graphs built from explicit elements. Later ones handle more complex dialogue, and the final sections combine AI agents with a RAG agent, followed by a testing segment. Each stage has a code walkthrough and an exercise, which makes the sequence easy to pause and repeat.
Welcome to this video course on LangGraph, the powerful Python library for building advanced conversational AI workflows. In this course, Vaibhav Mehra will teach you how to design, implement, and manage complex dialogue systems using a graph-based approach. By the end, you'll be equipped to build robust, scalable conversational applications that leverage the full potential of large language models.
Code: https://github.com/iamvaibhavmehra/LangGraph-Course-freeCodeCamp
Vaibhav Mehra on LinkedIn: https://www.linkedin.com/in/vaibhav-mehra-main/
Vaibhav on Instagram: https://www.instagram.com/iamvaibhavmehra/
❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp
⭐️ Contents ⭐️
0:00:00 Introduction
0:01:24 Type Annotations
0:08:35 Elements
0:18:39 Agent 1 Intro
0:21:08 Agent 1 Code
0:32:22 Agent 1 Exercise
0:33:07 Agent 2 Intro
0:34:02 Agent 2 Code
0:43:27 Agent 2 Exercise
0:44:29 Agent 3 Intro
0:45:18 Agent 3 Code
0:54:04 Agent 3 Exercise
0:55:36 Agent 4 Intro
0:56:37 Agent 4 Code
1:13:09 Agent 4 Exercise
1:14:14 Agent 5 Intro
1:15:45 Agent 5 Code
1:29:19 Agent 5 Exercise
1:31:01 AI Agent 1 Intro
1:32:49 AI Agent 1 Code
1:42:54 AI Agent 2 Intro
1:43:58 AI Agent 2 Code
2:03:20 AI Agent 3 Intro
2:05:00 AI Agent 3 Prerequisite
2:12:28 AI Agent 3 Code
2:28:46 AI Agent 4 Intro
2:30:59 AI Agent 4 Code
2:52:09 RAG Agent Intro
2:53:01 RAG Agent Code
3:06:15 RAG Agent Testing
3:09:04 Course Outro
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