Agentic AI in Healthcare Training Course
Agentic AI refers to a methodology where AI systems independently plan, reason, and utilize tools to achieve specific objectives within set boundaries.
This instructor-led, live training (available online or onsite) targets intermediate-level healthcare and data teams looking to design, evaluate, and govern agentic AI solutions for clinical and operational applications.
Upon completing this training, participants will be equipped to:
- Articulate agentic AI concepts and constraints within healthcare settings.
- Construct secure agent workflows incorporating planning, memory, and tool integration.
- Develop retrieval-augmented agents that process clinical documents and knowledge bases.
- Assess, monitor, and govern agent behaviour using guardrails and human-in-the-loop controls.
Course Format
- Interactive lectures complemented by facilitated discussions.
- Guided labs and code walkthroughs conducted in a sandbox environment.
- Scenario-based exercises focusing on safety, evaluation, and governance.
Customization Options
- To request customized training for this course, please get in touch with us to arrange your session.
Course Outline
Foundations of Agentic AI for Healthcare
- Distinguishing agentic systems from tool-only LLM applications
- Defining autonomy boundaries, policies, and human oversight
- Understanding the healthcare data landscape and constraints (EHR, FHIR, PHI)
Designing Agent Workflows
- Integrating planning, memory, tool use, and reflection loops
- Leveraging prompt engineering, functions/tools, and action selection
- Implementing state management and orchestration patterns
Retrieval-Augmented Agents
- Ingesting and chunking medical documents
- Utilizing embeddings, vector stores, and relevance evaluation
- Establishing grounding for responses and citation strategies
Healthcare Integrations and Interoperability
- Basics of FHIR/SMART for agent connectivity
- Managing structured and unstructured clinical data
- Handling eventing, APIs, and audit trails
Safety, Risk, and Governance
- Implementing guardrails, red-teaming, and fail-safe designs
- Managing PHI, de-identification, and access controls
- Facilitating human-in-the-loop review and escalation paths
Evaluation and Monitoring
- Conducting offline evaluations, establishing golden sets, and defining KPIs
- Detecting hallucinations and performing factuality checks
- Ensuring observability, logging, and managing cost/latency
Deployment Patterns and Hands-on Lab
- Comparing API-based vs. on-prem model choices
- Building a retrieval-augmented agent using LangChain, FastAPI, and ChromaDB
- Executing simulated incident response and rollback procedures
Summary and Next Steps
Requirements
- A foundational understanding of basic Python programming
- Prior experience with data analysis or machine learning workflows
- Familiarity with healthcare data concepts (e.g., EHR, FHIR)
Target Audience
- Healthcare data scientists and ML engineers
- Clinical informatics and digital health product teams
- IT leaders and innovation managers in the healthcare sector
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
Agentic AI in Healthcare Training Course - Enquiry
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