Udemy

Build intelligent Multi-Agent applications with AutoGen 0.7

Enroll Now
  • 878 Students
  • Updated 9/2025
4.4
(89 Ratings)
CTgoodjobs selects quality courses to enhance professionals' competitiveness. By purchasing courses through links on our site, we may receive an affiliate commission.

Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 56 Minute(s)
Language
English
Taught by
Amit Kumar Thakur
Rating
4.4
(89 Ratings)
5 views

Course Overview

Build intelligent Multi-Agent applications with AutoGen 0.7

Master AutoGen 0.6 to Build Scalable, Intelligent Multi-Agent AI Applications for Real-World Tasks

Microsoft has re-architected the AutoGen framework in version 0.4, and this course is entirely based on the updated version.


The future of AI is multi-agent collaboration, where intelligent agents work together to solve complex tasks efficiently. This course is designed to help you master the AutoGen framework (v 0.4+), a powerful tool for building and orchestrating AI agents that interact, reason, and collaborate. Whether you're an AI enthusiast, a developer, or a researcher, this course will equip you with the skills to build and deploy scalable multi-agent applications.

What You Will Learn

  1. Fundamentals of Multi-Agent Systems – Understand the core components of AI agents, their use cases, and how they enhance AI-driven workflows.

  2. Setting Up Your Development Environment – Learn how to install Python, set up VS Code, create virtual environments, and install necessary dependencies.

  3. Deep Dive into AutoGen – Explore AutoGen’s architecture, libraries, and capabilities, including working with OpenAI and open-source LLaMA models.

  4. Key AutoGen Concepts – Master agent messaging, user proxy agents, assistant agents, streaming responses, and multi-modal AI integration.

  5. Team-Based AI Agent Collaboration – Learn how to organize AI agents into teams, define termination conditions, and implement SelectorGroupChat for LLM-based agent selection.

  6. Advanced Multi-Agent Concepts – Explore state management in AI workflows and dive into Magentic-One, a generalist multi-agent system for web and file-based tasks.

  7. Hands-On Projects – Implement real-world AI agent applications, including:

    • Project 1: Develop a Streamlit-based AI Agent App, understand and optimize code with agent

    • Project 2: Build a Multi-Agent AI Chatbot for Customer Support that interacts with users of ecommerce portal and processes queries dynamically.


Who Should Take This Course?

  • AI & ML practitioners looking to build intelligent AI agents

  • Developers interested in AutoGen, AutoGen  AgentChat and AI automation

  • Researchers exploring multi-agent collaboration

  • Anyone eager to develop AI-powered applications

By the end of this course, you will have hands-on experience building and optimizing AI-driven multi-agent systems using AutoGen, setting you up to develop next-gen AI solutions.

Course Content

  • 9 section(s)
  • 44 lecture(s)
  • Section 1 Introduction
  • Section 2 Introduction to Multi-Agent Systems and Autogen
  • Section 3 LLM Models
  • Section 4 Important AutoGen Concepts
  • Section 5 Project 1 - Streamlit App with AI Agent: Code Walkthrough & Optimization
  • Section 6 Teams: Organizing Agents for Collaborative Tasks
  • Section 7 Project 2: Multi-Agent AI Chatbot for Customer Support
  • Section 8 Advanced Concepts in Multi-Agent Systems
  • Section 9 Thank you and further actions

What You’ll Learn

  • Understand Multi-Agent Systems – Learn the fundamentals of multi-agent architectures, their advantages, and real-world applications in AI-driven workflows.
  • Hands-on with AutoGen – Gain practical experience in using AutoGen 0.4 and 0.5 to build and customize intelligent multi-agent applications for problem-solving
  • Agent Collaboration & Communication – Explore how multiple AI agents interact, share knowledge, and coordinate tasks efficiently using structured protocols
  • Building Scalable AI Applications – Develop AI solutions for real-world scenarios, such as customer support

Reviews

  • P
    Pankaj Chhatri
    4.0

    I liked the content. Could be great with more advanced concepts.

  • A
    Ali Babalhavaeji
    4.5

    very good line by line explanation of codes, and good combination of theory and hands-on

  • T
    Thiyaneshwar K
    5.0

    Good.

  • K
    Kazım Berk Küçüklerli
    4.0

    Language can be improved. It is really hard to understand.

Start FollowingSee all

We use cookies to enhance your experience on our website. Please read and confirm your agreement to our Privacy Policy and Terms and Conditions before continue to browse our website.

Read and Agreed