The Future is Now: AI Tools and Applications for Healthcare Professionals - Certificate Workshop

Over six immersive sessions, learners will blend strategy and technical practice, building toward a healthcare-specific capstone project and an online exam.

Those who complete both will earn a Certificate of Completion in Generative & Agentic AI in Healthcare.

Target Audience
Healthcare executives, administrators, and clinical leaders with a technical background or familiarity with AI concepts, seeking to apply Generative and Agentic AI responsibly in their organizations.

Course Format

• Total Time: 18 hours (Six 3-hour sessions)
• Mode: Hybrid (Live + Online Components)
• Capstone Project: Prototype a healthcare-specific AI-powered workflow or tool
• Assessment: Online exam + capstone demo
• Tools: OpenAI API, Hugging Face, Google Forms, Airtable, synthetic healthcare datasets

By the end of the course, participants will have the opportunity to: 

1. Understand the fundamentals of Generative and Agentic AI systems and their applications in healthcare.
2. Use prompt engineering and fine-tuning techniques for clinical, operational, and research use cases.
3. Build lightweight agentic workflows using no-code/low-code platforms like n8n.
4. Evaluate compliance and risk factors (HIPAA, FDA SaMD, Responsible AI).
5. Design and deliver a working healthcare automation or intelligent tool as a capstone project.

Key Takeaways

• Grasp the fundamentals of generative and agentic AI in healthcare.
• Design and implement functional healthcare-specific AI workflows.
• Integrate AI responsibly into clinical, research, and operational settings.
• Deliver a working, responsible AI solution with measurable impact.

Session Breakdown:
 

Session 1: Foundations of Generative and Agentic AI in Healthcare

Narrative:
This session lays the foundation for the course by introducing the fundamentals of Generative and Agentic AI, with a healthcare-specific lens. Executives will explore how the theoretical foundation for these technologies, current advances and applications, and how they are currently being applied in medicine. The session also grounds participants in the ethical and regulatory responsibilities that come with AI deployment.

Topics:

• Generative AI in healthcare: text, imaging, and data synthesis
• Agentic AI and autonomous workflows in hospitals and clinics
• Overview of Foundation models (ChatGPT, Claude, Gemini, Med-PaLM)
• Responsible AI principles in healthcare: safety, bias, explainability, compliance

Hands-On Activities:

• Prompt chains for summarizing de-identified patient notes
• Ethical case study: risk of hallucinations in automated triage

Session 2: Tools for Building Workflows and Agents

Narrative:
This session introduces the platforms and tools that enable healthcare leaders to build intelligent workflows. Participants will gain familiarity with low-code/no-code automation engines and learn the basics for how to integrate large language models into clinical and operational processes.

Topics:

• Workflow engines as agentic frameworks (n8n, LangChain, Zapier)
• Anatomy of automation: triggers, AI processing, outputs
• Building modular workflows for scalability

Hands-On Activities:

• Build a patient intake workflow: Google Form submission --> OpenAI summary --> Auto-generated email response

Session 3: Clinical Applications and Workflow Integration

Narrative:
This session applies AI concepts directly to frontline care. Executives will see how generative AI can assist clinicians in documentation, triage, and clinical decision support (while respecting regulatory limits and clinician autonomy). Emphasis will be placed on safe integration with existing electronic health records and clinical processes.

Topics:

• Clinical documentation automation (Automating SOAP note summarization)
• AI-enabled triage assistants and decision support
• Integration challenges with EHRs (Epic, Cerner)
• Guardrails for safety and clinical reliability

Hands-On Activities:

• Build a documentation assistant for clinical notes
• Peer review for reliability and compliance

Session 4: Administrative and Operational Use Cases

Narrative: 
This session explores how AI-driven automation can reduce inefficiencies in billing, coding, scheduling, and workforce management that plague the complex operations of Healthcare organizations. Participants will design workflows that directly address burnout and cost savings in administrative processes.

Topics:

• Claims-to-coding automation (ICD-10 summarization)
• Scheduling optimization and workforce management
• Revenue cycle management with AI-driven insights
• Dashboards for patient satisfaction and quality metrics

Hands-On Activities:

• Automate a claims-to-code summarization workflow
• Create a dashboard for patient feedback analysis

Session 5: Research, Data Analytics, and Knowledge Management

Narrative:
This session focuses on research and knowledge workflows. Generative AI can accelerate evidence synthesis, literature reviews, and knowledge sharing across institutions. Executives will learn to leverage AI for both structured (clinical trials) and unstructured (publications, notes) data.

Topics:

• Automating systematic literature reviews
• Semantic search across PubMed and clinical guidelines
• Multimodal AI in imaging, genomics, and clinical trials
• Turning unstructured data into institutional knowledge

Hands-On Activities:

• Build a PubMed summarizer into an Airtable research tracker
• Experiment with embeddings for guideline search

Session 6: Risk, Governance, and Capstone Preparation

Narrative:
The final session prepares participants to deploy AI responsibly and to finalize their capstone projects. It introduces governance models, regulatory frameworks, and strategies for communicating AI adoption to boards, regulators, and clinical teams. The session culminates with capstone build time and peer feedback.

Topics:

• Governance playbooks for healthcare AI adoption
• Regulatory Considerations for Adoption (HIPAA, FDA SaMD, and EU AI Act)
• Vendor risk management and procurement strategies
• Emerging frontiers: federated learning, digital twins, agentic triage systems
• Capstone project build session and peer review

Hands-On Activities:

• Bias audit of a synthetic patient dataset

Assessment

• Verified Completion of all Weekly Coding Projects: 60% of final score
• Online multiple-choice quiz: 40% (Ethics, LLM basics, workflow logic)

Participants must bring a laptop to all training sessions held in person. 

This requirement does not apply to sessions conducted via Zoom.

Participants will receive full access to the AI tools used throughout the class, at no extra cost, for the duration of the training.