Build intelligent Multi-Agent applications with AutoGen 0.4
Published 4/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 56m | Size: 1.66 GB
Master AutoGen 0.4 to Build Scalable, Intelligent Multi-Agent AI Applications for Real-World Tasks
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 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
Requirements
Python Basics
Description
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, 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 LearnFundamentals of Multi-Agent Systems - Understand the core components of AI agents, their use cases, and how they enhance AI-driven workflows.Setting Up Your Development Environment - Learn how to install Python, set up VS Code, create virtual environments, and install necessary dependencies.Deep Dive into AutoGen - Explore AutoGen's architecture, libraries, and capabilities, including working with OpenAI and open-source LLaMA models.Key AutoGen Concepts - Master agent messaging, user proxy agents, assistant agents, streaming responses, and multi-modal AI integration.Team-Based AI Agent Collaboration - Learn how to organize AI agents into teams, define termination conditions, and implement SelectorGroupChat for LLM-based agent selection.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.Hands-On Projects - Implement real-world AI agent applications, including
roject 1: Develop a Streamlit-based AI Agent App, understand and optimize code with agentProject 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 agentsDevelopers interested in AutoGen, AutoGen AgentChat and AI automationResearchers exploring multi-agent collaborationAnyone eager to develop AI-powered applicationsBy 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. Who this course is for
This course is designed for AI enthusiasts, GenAI practitioners, software developers, and machine learning practitioners who want to build intelligent multi-agent applications using AutoGen.
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