AI Agent Teams: Build Multi-Agent Systems with AutoGen and Python

AI is evolving from single-prompt assistants to collaborative teams of specialized agents that work together to solve complex tasks. This course teaches you how to design, build, and orchestrate these autonomous multi-agent systems from scratch. You will transition from writing simple API calls to engineering coordinate agent networks that communicate, share workloads, and execute multi-step workflows. By reading through practical, step-by-step text explanations and clean code walkthroughs, you will gain the skills to build interactive web frontends for your agents and prepare them for real-world deployment. What you'll learn: - Understand the foundational concepts of LLM agents, prompt engineering for agent personas, and multi-agent communication patterns. - Configure autonomous agent teams using AutoGen to collaborate and solve complex tasks without manual intervention. - Build an interactive web interface using Streamlit to easily converse with and monitor your agent networks. - Apply modern Python development practices, including virtual environments and structured API calls, to ensure clean and maintainable code. - Deploy your multi-agent applications to a cloud platform so users worldwide can access your AI-powered services. - Integrate secure payment processing with Stripe to prepare your application for subscription-based monetization. The course starts with basic agent definitions and API setups before guiding you through building local agent teams, designing user interfaces, and finally deploying your completed system to the cloud. This course is designed for Python beginners, aspiring AI developers, and tech enthusiasts who want to explore the future of autonomous software. No advanced machine learning background is required. Start reading today to build your first team of cooperative AI agents.