What you'll learn

  • Key principles, technical aspects and potential pitfalls of deep learning and emerging AI approaches
  • Which problems are best suited for an AI solution and how AI adds value, drawing from established examples
  • Operational aspects and real-world AI implementation, such as data infrastructure and quality, annotation (e.g., clinical, biological or chemical), workflow integration, human/computer interface and regulatory pathways
  • Organizational needs, capabilities and structure to leverage AI in a variety of contexts (from large organizations to start-ups)
  • How to anticipate and address bias in AI

Course description

Applications of artificial intelligence in health care are expanding rapidly. Despite its great long-term potential, risks and challenges remain for both AI developers and their partners in health care, the life sciences industry and digital health. 

This program will allow leaders across the ecosystem to gain insights into what it takes to successfully utilize AI in the unique cultural, economic and regulatory context of health care. Interactive sessions will address technical concepts as well as real-world implementation, with examples drawn from health care delivery/operations and drug development. 

The curriculum will feature a combination of live virtual class sessions, small group application exercises, pre-work and vigorous discussions. Upon completion of the program, participants will be able to immediately apply insights gained to the fast-moving and complex health care sector. A certificate of completion will be provided. 


  • Associate Dean for Executive Education, Harvard Medical School
  • Head of Machine Learning, Generate Biosciences; Assistant Professor, Harvard T.H. Chan School of Public Health, Harvard Medical School
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