This course teaches you how to assess and improve the quality, safety, and business impact of the AI agents you create. You will learn straightforward techniques for evaluating outputs, measuring reliability, and reducing hallucinations and errors. The course covers beginner friendly security, privacy, and governance practices so your agents align with organizational policies and regulations. You will design simple experiments to compare processes with and without agents, quantify time savings, and communicate results to managers. Finally, you will explore how to maintain, document, and responsibly scale your agents without creating unmanageable “agent sprawl.” By the end, you will be able to define clear output requirements, evaluate your agents systematically, and make evidence based decisions about when and how to deploy them.
What you'll learn
techniques for evaluating AI outputs
methods to measure the reliability of AI agents
strategies for reducing AI errors and hallucinations
beginner-friendly practices for AI security and governance
designing experiments to compare AI-assisted processes