Completed the AI Agents foundation training: what agents are, how they differ from chatbots, models, tools and memory, writing effective instructions, task-based vs autonomous agents, finding the right opportunities, testing, and responsible, secure use of data.

Built a working AI agent and submitted a portfolio explaining its purpose, how it was built and tested, the measurable benefit it delivers, how data and access are kept secure, and lessons learned. Reviewed evidence that the agent worked. Passed with at least 80% against a published rubric.

Passed a scenario-based knowledge check on AI agent fundamentals, covering agent design, instructions, guardrails, human oversight, testing and monitoring, and data privacy. Scored at least 17 out of 21 (80%).

Completed a capstone project designing an AI agent solution, either for a client or as an agent team for their own business. It covered needs analysis, diagnosis of the right tasks (and the wrong ones), agent design, rollout and benefits, and security. Passed with at least 80% against a published rubric