Building AI Agents & Agentic AI System via Microsoft Autogen

<div>Welcome to “Building AI Agents and Agentic AI Systems Using AutoGen”, a hands-on, project-driven course designed to help you master the future of intelligent software: Agentic AI. As large language models (LLMs) become more powerful, the next evolution is enabling them to work collaboratively through AI agents—and this course is your complete guide to making it happen using Microsoft's AutoGen framework.</div><div><br></div><div>Whether you're a data scientist, ML engineer, AI researcher, or product builder, this course will take you step-by-step into the world of multi-agent AI systems. You’ll learn to design, build, and deploy AI agents that can autonomously plan, reason, and execute complex tasks by communicating with each other and interacting with external tools.</div><div><br></div><div>What you’ll learn:</div><div><ul><li><span style="font-size: 1rem;">Understand the fundamentals of Agentic AI and how it differs from traditional GenAI applications.</span></li><li><span style="font-size: 1rem;">Explore the architecture of AutoGen and how it orchestrates multiple LLM-powered agents to collaborate effectively.</span></li><li><span style="font-size: 1rem;">Build and customize various types of agents (e.g., UserProxyAgent, AssistantAgent, GroupChatAgent).</span></li><li><span style="font-size: 1rem;">Implement multi-agent workflows that solve real-world problems with code generation, task breakdown, and dynamic decision Making.</span></li><li><span style="font-size: 1rem;">Integrate tools like web APIs, databases, and Python functions into your agent ecosystem.</span></li><li><span style="font-size: 1rem;">Use AutoGen Studio for visual development and monitoring of agent interactions.</span></li><li><span style="font-size: 1rem;">Optimize agents for cost, speed, and performance using configuration tuning and role specialization.</span></li><li><span style="font-size: 1rem;">Deploy agentic systems for use cases like coding assistants, research bots, multi-agent chat applications, and automated task runners.</span></li></ul></div><div><span style="font-size: 1rem;">This course is project-focused—you won’t just learn the theory, you’ll build powerful agentic AI applications from scratch. You’ll understand how to design autonomous AI teams that mirror human workflows, assign responsibilities, communicate efficiently, and adapt to dynamic tasks.</span></div><div><br></div><div>We’ll also compare AutoGen with other orchestration frameworks like LangChain and CrewAI, giving you a well-rounded perspective of what tools to use and when.</div><div><br></div><div>Who should take this course?</div><div><br></div><div>This course is ideal for:</div><div><ul><li><span style="font-size: 1rem;">ML and AI professionals wanting to transition into LLM-powered agentic development.</span></li><li><span style="font-size: 1rem;">Developers interested in building intelligent apps that go beyond chatbots.</span></li><li><span style="font-size: 1rem;">GenAI enthusiasts eager to push the limits of LLM capabilities using agent collaboration.</span></li><li><span style="font-size: 1rem;">Startup founders and product teams working on AI-first applications.</span></li><li><span style="font-size: 1rem;">Students and researchers looking to build hands-on projects with cutting-edge agentic frameworks.</span></li></ul></div><div><span style="font-size: 1rem;">By the end of this course, you will have the confidence and skills to build, scale, and deploy AI agent ecosystems that can reason, act, and collaborate just like teams of humans—powered by the latest advancements in AutoGen and Agentic AI.</span></div>

What you'll learn:

• Understand the fundamentals of agentic AI and how autonomous agents interact using the Microsoft AutoGen framework.
• Set up and configure AutoGen to build AI systems with multiple collaborative agents.
• Design and implement custom agents that perform tasks like coding, reasoning, and decision-making.
• Build and deploy real-world multi-agent workflows that automate complex tasks end-to-end.