Multimodal Agent Testing and Deployment

This course covers testing, guardrails, and deployment for multimodal agents. Evaluating open-ended behavior and operating agents safely are the two areas where applied agent projects most often fail. You start by writing tests for agent responses and building evaluation criteria for behavior that has no single correct answer. You then implement input and output guardrails, log decision traces so agent choices can be audited, and apply responsible AI practices covering bias, transparency, and disclosure. The course closes with deployment: Streamlit interfaces, REST APIs, and containers, alongside the operating concerns of latency, token cost, and rate limiting, applied through builds including support ticket triage, visual search, and a voice-driven assistant. By the end of this course, you will be able to: - Write tests and evaluation criteria for open-ended agent responses. - Implement input and output guardrails that block unsafe or invalid behavior. - Log and audit agent decision traces. - Apply responsible AI practices for bias, transparency, and disclosure. - Deploy agents using Streamlit, REST APIs, and containers. - Measure and manage latency, token cost, and rate limits. Intended for learners who have completed the earlier courses in the Specialization. Enroll now to make your agents testable, safe, and ready for other people to use.