Biomedical Data Science Curriculum Initiative

The realization that effective use of data to open up new directions in biomedical investigation and clinical care is a crucial skill for the biomedical workforce has led to a rapid growth of new educational offerings in biomedical data science. Many new graduate programs in data science and informatics with applications in healthcare, translational science, clinical research, and public health have been created in recent years. The rapid evolution of this field is creating opportunities but also challenges for educators, students, and employers alike.

  • What should a biomedical data science program teach?
  • What skill set should a biomedical data scientist possess?
  • How can biomedical data science be taught effectively to a diverse student body?
  • What kind of background is required to succeed in a biomedical data science graduate program?

To address these questions, we propose to develop a set of guidelines and recommendations for a biomedical data science graduate-level core curriculum and educational resources to teach such a curriculum.

We have created a cross-institutional working group of US-based data science educators with expertise in healthcare, translational science, clinical research, and public health that includes representatives from National Library of Medicine-funded T15 training programs. Through a series of conference calls and workshops, this working group will develop and publish recommendations as an offering to the biomedical data science community.


This project is led by Nils Gehlenborg and Alexa T McCray (Co-PIs of the NLM T15 Training Grant).


The Biomedical Data Science Curriculum Initiative is supported by the National Library of Medicine through a T15 Training Grant Supplement and by the Department of Biomedical Informatics at Harvard Medical School.