Description
Multi-Agents with LangChain & LangGraph: Build 4 Projects. This course explores how to design, develop, and manage AI Multi-Agent Systems using LangChain and LangGraph tools through the construction of four real-world projects. This project-based training takes students to the new frontiers of AI orchestration. Modern AI development has shifted from simple single-agent systems to multi-agent systems (MAS), complex networks of specialized agents that work together to solve complex problems. This course is designed to move the audience from simple single-agent demos to building autonomous agent teams to solve real-world challenges. The course begins with a theoretical dissection, and software architects gain a deep understanding of the structure of multi-agent systems, how agents communicate with each other, share state, and make decisions. The instructor doesn’t just show code, but also explores the four essential multi-agent design patterns in LangChain to fully understand the logic behind each architecture. The core of this learning platform is hands-on, with learners implementing four distinct, real-world projects. These projects include building an intelligent travel planner using the Sub-Agents pattern and designing a job application pipeline using the Handoff pattern. In the process, state management, loop routing, and implementing human-in-the-loop interactions using LangChain and LangGraph are taught. By the end, participants will have a portfolio of advanced multi-agent projects on their resume and will have the skills to architect custom AI solutions for various industries to succeed in business process automation or building the next generation of intelligent assistants.
What you will learn
- Mastering Design Patterns: Learn all 4 design patterns for multi-agent systems (such as Sub-Agents and Hand-off) using LangChain and LangGraph to produce commercial-grade AI.
- Building an intelligent travel planner: Implementing a complex system with a sub-agent pattern to coordinate specialized tasks across multiple AI nodes.
- Job application pipeline development: Create an automated process for submitting job applications using a delegation pattern to seamlessly transfer statuses between agents.
- Project Architecture and Deployment: Design and launch 4 real-world projects that demonstrate the practical application of Multi-Agent Systems (MAS).
This course is suitable for people who:
- AI Engineers: Professionals who want to move beyond single-agent systems and into complex, multi-stage agent workflows.
- Software Developers: Programmers who want to master LangChain and LangGraph to build controllable and stateful AI applications.
- Technical Architects: Individuals responsible for designing multi-agent systems for enterprise-level automation.
- LangChain enthusiasts: Developers who are ready to upgrade their workflow from simple linear chains to cyclic and graph-based architectures.
Course Details Multi-Agents with LangChain & LangGraph: Build 4 Projects
- Publisher: Udemy
- Instructor: Fikayo Adepoju
- Training level: Beginner to advanced
- Training duration: 12 hours and 37 minutes
- Number of lessons: 52
Course topics
Prerequisites for the Multi-Agents with LangChain & LangGraph: Build 4 Projects course
- 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.
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 1080p
Download link
Rapidgator link
File(s) password: www.downloadly.ir
File size
7.1 GB
