Agentic AI: Foundations and Applications

(3 Credit Hours) · Undergraduate

As AI systems move beyond generating responses to taking coordinated, multi-step actions in the real world, this course prepares students to design, build, and work effectively with agentic systems. Starting with a working understanding of how large language models and retrieval-augmented generation function, students progress through the key components of modern agent systems — including how they connect to external tools, manage complex workflows, and coordinate with one another to accomplish goals. Core topics include prompt engineering, context management, tool integration, agent communication, and orchestration across multi-agent pipelines. Throughout the course, students complete hands-on projects using current platforms and frameworks, with an emphasis on design principles that remain relevant as the technology continues to evolve. Prior completion of at least one semester of Python programming is required.