Building Multi-Agent Systems with AutoGen and Python

AI is moving beyond single-prompt interactions into collaborative ecosystems where multiple agents work together. If you want to orchestrate intelligent AI conversations, the AutoGen framework is a powerful starting point. In this text-based course, you will learn how to design, configure, and manage multi-agent systems in Python. You will start with foundational AI concepts and terminology, then progress to writing code for custom agents that can communicate, execute tasks, and retrieve information to solve problems autonomously. What you'll learn: • Understand the foundational concepts of multi-agent systems and AI orchestration. • Configure your Python environment using modern packaging tools and virtual environments. • Build and customize conversational agents using the AutoGen framework. • Implement Retrieval-Augmented Generation (RAG) patterns to give agents external knowledge. • Apply prompt engineering basics to guide agent behavior and collaboration. • Practice coordinating complex workflows through written code exercises. The course flows logically from essential definitions and basic agent setup to more advanced collaborative patterns. You will read through clear explanations, study practical Python snippets, and reinforce your skills through structured written exercises. This course is designed for beginners and Python developers looking to explore agentic AI without needing prior machine learning expertise. Start reading today to build your first team of collaborative AI agents.