Overview
Earn your certificate in Agentic AI for Healthcare. This hands-on online program introduces how AI agents, tool-using large language models, and multi-agent workflows can be designed, evaluated, and responsibly deployed in healthcare settings.
Through interactive Jupyter notebooks, learners will explore how agentic AI systems move beyond one-time chatbot responses to plan, act, use tools, coordinate across tasks, and adapt over time within defined safety boundaries. The course begins with the foundations of agentic AI, including agents, task decomposition, tool use, and degrees of autonomy, then builds toward practical healthcare applications such as clinical workflow coordination and hospital discharge support.
Learners will study core agentic design patterns including reflection, planning, ReAct, tool use, and multi-agent collaboration. They will compare single-agent and multi-agent systems, examine communication patterns such as linear, hierarchical, and all-to-all coordination, and apply these ideas to realistic healthcare workflows. The course also includes a practical building module where learners construct a multi-agent hospital discharge system using mock EHR data, specialized agents, guardrails, verification steps, and end-to-end workflow orchestration.
Because agentic AI systems can make decisions, call tools, and influence real-world outcomes, the course also emphasizes responsible design. Learners will examine safety, privacy, fairness, transparency, accountability, human oversight, reliability, security, and deployment readiness in high-stakes healthcare environments.
By the end of the course, learners will understand not only what agentic AI is, but how to design, build, evaluate, and govern agentic systems for healthcare use cases where trust, safety, and human oversight are essential.
Modules included
- Introduction to Agentic AI
Agents, LLM-to-agent workflows, task decomposition, tool use, and autonomy. - Ethics of Agentic AI
Safety, privacy, fairness, transparency, accountability, human oversight, failure modes, risk classification, and responsible deployment. - Agentic AI Design Patterns
Reflection, tool use, planning, multi-agent collaboration, ReAct, and when agents are the right fit. - Agentic AI in Healthcare
Single-agent vs. multi-agent systems, agent communication patterns, the agent loop, and clinical workflow coordination.
Building Agentic AI in Healthcare
A hands-on hospital discharge project using mock EHR data, specialized agents, guardrails, verifier agents, and end-to-end orchestration.
