The purpose of this course is to provide a comprehensive understanding of AI agents, demonstrate their use in workflows, and delve into Autogen.
In this course, you’ll explore the foundations of AI agents — from how they reason and communicate to how they collaborate in structured workflows. Through practical, real-world projects, you’ll learn to design and deploy agents capable of decision-making, retrieval-augmented generation (RAG), tool use, and adaptive behavior. We’ll dive deep into enhanced inference techniques, prompt templating, memory strategies, and teachable agents — giving you the tools to optimize performance and tailor agents to specific tasks.
Through detailed walkthroughs, code samples, and project templates, you’ll learn to:
- Build and configure AI agents with defined goals and tools
- Create agent workflows that mimic human-like collaboration
- Use RAG to improve performance with external knowledge
- Apply prompt engineering and memory strategies for smarter behavior
- Develop teachable agents that grow more capable with user input
By the end of the course, you’ll be able to create your own autonomous systems that automate tasks, assist users, and solve complex problems — all using the power of AI agents and Autogen.
We will also be updating this course with bonus content on a regular basis as the AI sector is ever burgeoning.
Whether you’re an AI enthusiast, software developer, data scientist, or aspiring agent engineer, this course will give you the practical tools and conceptual knowledge to build the next generation of intelligent applications.
- Beginner software developers who want to leverage AI agents in their workflows
