Trusted by leaders at Mayo Clinic, Eli Lilly, and Mass General Brigham
Early Bird ends in:
Course starts Mar 31
2.5-WEEK AI INTENSIVE
HEALTHCARE
STARTS MAR 31
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Duration
2.5 Weeks
FORMAT
Live + AI-Guided
TUITION
$1,595 $1,995
Save $400
Built on the Agentic AI Intensive—named by Forbes as a top course to master AI agents.
Get the full curriculum, faculty details and pricing instantly.
Health Systems
Specialty Practices
Pharma* & Biotech
Healthcare Consulting
Leaders from Kaiser Permanente, Gilead Sciences, Becton Dickinson, Novartis, Novavax, and Grifols have completed our programs.
*examples focus on practical agentic AI frameworks applied to health systems, clinical care pathways, and pharmaceutical workflows.
“Understanding how to apply the AGENT framework and how to embed human-in-the-loop oversight fundamentally changed how I approach AI systems in healthcare.”
“I've already prototyped a multi-agent system for addiction medicine consults and integrated what I learned into an NSF proposal.”
Strategy and implementation frameworks for non-technical leaders in regulated environments.
Design workflows with PHI protections built in
Evaluate AI pilots for clinical safety and regulatory fit
Explain how agents change workflows, risk, and accountability
Brief technical teams with implementation-ready specs
Two implementation-ready documents you build during the program, ready to present to leadership, your team or client.
DELIVERABLE 1
Your organization’s AI vision and opportunity map — ready to present to stakeholders.
01
Opportunity Scan — Where AI creates value across your workflows
02
Prioritization Matrix — Which opportunities to pursue first
03
Strategic Rationale — Why AI, why now, and where you're heading
DELIVERABLE 2
A complete workflow redesign—ready for compliance review and technical handoff.
01
Workflow Redesign — Current state → agent-first design
02
Governance Structure — Human-in-the-loop protocols, compliance requirement mapping, accountability framework
03
Implementation Roadmap — Pilot plan with success metrics
See the full curriculum and example deliverables in the course outline →
Apply what you learn to the workflows that matter in your setting
Pre-visit symptom assessment and clinical routing
Insurance verification and approval workflow
Eligibility screening and enrollment workflow
Access control, audit logging, compliance monitoring
Not pre-recorded videos with generic case studies. A curriculum that responds to your context.
AI-generated audio summaries and readings tailored to your progress and role
Trained on the curriculum and your deliverables—available 24/7 for guidance
Direct interaction with Harvard and HMS faculty, and HDSR Board Members - not pre-recorded
Your workflows, your compliance requirements, your strategy—not hypotheticals
Three phases. A clear arc from understanding to implementation.
PHASE 1
Agentic AI, ethics & value chain analysis
Conceptual, historical, and ethical perspectives
PHASE 2
AGENT framework & workflow redesign
Organizational, clinical, and operational perspectives
PHASE 3
Impact evaluation & change leadership
Data-analytical perspective
Get the detailed week-by-week schedule →
Upon completion, receive a Certificate of Completion from Harvard Data Science Initiative recognizing your proficiency in healthcare AI workflow design.
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Named by Forbes as a top course to master AI agents
“The most interactive, hands-on AI learning I've had in any coursework—and I have a PhD and master's in medical informatics.”
“The AGENT method gave me a structured, repeatable way to evaluate use cases. I feel ready to lead agentic AI projects.”
“Architecting agentic workflows, evaluating safety and governance—these are execution tools already driving impact in my work.”
Harvard faculty, Harvard Data Science Review board members, and industry practitioners bridging data science, healthcare, and AI strategy.
Curriculum based on Harvard Data Science Review research including the special issue “Future Shock: Grappling With the Generative AI Revolution.”
Whipple V. N. Jones Professor of Statistics, Harvard University
Founding Editor-in-Chief of Harvard Data Science Review and former Dean of Harvard Graduate School of Arts and Sciences. Recipient of the COPSS Presidents' Award and elected member of the American Academy of Arts and Sciences. Pioneers advances in statistical methodology, data quality assessment, and the foundational principles of data science.
Daniel C. Tosteson Professor of Health Care Policy, Harvard Medical School
Associate Editor at Harvard Data Science Review and Professor at the Harvard T.H. Chan School of Public Health. Recipient of the 2025 ASA Health Policy Statistics Mid-Career Excellence Award. Drives innovation in causal inference methods, data science foundations, and AI evaluation to advance healthcare.
Associate Professor of Communication, Simon Fraser University
Co-editor of the "Mining the Past" column at Harvard Data Science Review and former Junior Fellow with the Harvard Society of Fellows. Co-organizer of the Cambridge Mellon Sawyer Seminar, "Histories of AI: A Genealogy of Power." Provides historical context for the agentic AI era and ethical frameworks for AI governance in healthcare.
Associate Professor of Health Care Policy and Medicine, Harvard Medical School
Primary care physician at Massachusetts General Hospital and Associate Editor of JAMA Health Forum. Former Medicare policy advisor at the U.S. Department of Health and Human Services. Bridges health economics and clinical practice to illuminate the policy landscape for AI adoption in healthcare.
Co-Founder & CEO, DAIN Studios Finland
Harvard Data Science Review Board Member and co-creator of the AGENT Framework. Previously headed data and AI departments at Sanoma Media and Nokia. Leads hands-on sessions on agentic workflow design and enterprise AI strategy.
Co-Founder & CEO, DAIN Studios Germany
Harvard Data Science Review Board Member and co-creator of the AGENT Framework. Previously headed global data and AI initiatives at Siemens, Nokia, and Deutsche Telekom. Leads hands-on sessions on agentic workflow design and enterprise AI transformation.
Get full faculty bios and session details in the course outline →
View the outline to see the complete curriculum and application process.
Live with HDSR Faculty
Weekly sessions, not recorded lectures
AI-Personalized Learning
Adapts frameworks to your context
Agentic AI Focus
Not in most programs
Applied Outputs
Real strategy docs
No. You’ll design workflows, not code them. Your technical teams implement what you design.
Compliance is woven throughout—PHI protections, audit trails, and human-in-the-loop controls are core to every framework.
No. This program focuses on healthcare operations and workflows—not diagnostic medicine or clinical decision support. If you're looking to improve diagnostic accuracy or clinical decision-making at the point of care, this isn't the right fit. If you're interested in how AI transforms operational infrastructure (intake, authorization, documentation, coordination), this is purpose-built for that.
Yes. AI tutoring personalizes frameworks to your context—health system, specialty practice, payer, or life sciences.
Recordings available within 2 hours. Most learning is asynchronous, at your pace.
Healthcare-specific: clinical and operational examples, PHI requirements, and regulatory frameworks built into every module.
8–12 hours per week. About 2 hours daily of self-paced work, plus 60–90 minute live sessions on Tuesdays and Thursdays.
The core AGENT Framework applies globally. Regulatory examples focus on US requirements (HIPAA, FDA, state laws). International participants successfully apply the methodology to their own regulatory contexts.
Have more questions? The course outline includes detailed program information →
View the course outline to see the full curriculum, clinical examples, and how AI personalization works for your context.
2.5 Weeks
Duration
$1,595
Tuition
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Mar 31
Course Starts
Get the full curriculum, faculty details, and pricing instantly.