Multi-Agents with LangChain & LangGraph: Build 4 Projects

LangChain多智能体实战：4个项目精通设计模式

掌握LangChain与LangGraph构建多智能体系统的4种核心设计模式，通过智能旅行规划、自动化求职管道等真实项目，学会生产级AI系统的架构与部署。

Published 5/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 12h 37m | Size: 7.21 GB

Master Multi-Agent Design Patterns by Building Complex, Stateful, Real-World Projects with LangChain & LangGraph

What you’ll learn
Master all 4 Multi-Agent Design Patterns (Sub-Agents, Hand-off, etc.) using LangChain and LangGraph for production-grade AI.
Build a complex Smart Travel Planner using the Sub-Agents pattern to coordinate specialized tasks across multiple AI nodes.
Develop an automated Job Application Pipeline utilizing the Handoff pattern for seamless state transitions between agents.
Architect and deploy 4 real-world projects that demonstrate the practical application of Multi-Agent Systems (MAS).

Requirements
Proficiency in Python: You should be comfortable with asynchronous programming and decorators.
LangChain Basics: Prior experience with LangChain agents, prompts, and basic tool calling is required.
API Fundamentals: An active OpenAI or Anthropic API key to run and test your agents.
Logic & Flow: A basic understanding of graphs in LangGraph and state management is helpful but not mandatory.

Description
Welcome to the frontier of AI orchestration. Modern AI development is moving away from simple, single-agent systems toward Multi-Agent Systems (MAS)—complex networks of specialized agents that collaborate to solve sophisticated problems. This project-based course is designed to take you from a cool one-shot agent demos to building autonomous Agentic teams that solve real-world problems.

We begin by deconstructing the theory. You will gain a deep architectural understanding of Multi-Agent Systems, exploring how agents communicate, share state, and make decisions. We don’t just show you code; we dive into the four essential Multi-Agent Design Patterns in LangChain, ensuring you understand the “why” behind every architecture.

The core of this course is hands-on. You will build four distinct, real-world projects that implement these patterns. From a Smart Travel Planner using the Sub-Agents Pattern to a Job Application Pipeline utilizing the Handoff Pattern, you will learn how to manage state, handle cycles, and implement human-in-the-loop interactions using LangChain & LangGraph.

By the end of this course, you won’t just know how to use LangChain; you will have a portfolio of advanced Multi-Agent projects and the skills to architect bespoke AI solutions for any industry. Whether you are automating business processes or building the next generation of AI assistants, this course is a perfect fit for you.

See you in class.