Collaborative Data Science for Healthcare

Two hands holding a computer screen showing a silhouette of a human body, a line chart, and a data field.

Big data is proliferating in diverse forms within the field of healthcare, particularly in the use of electronic health records. (Image by mcmurryjulie from Pixabay.)


MIT Course Number


As Taught In

Fall 2020



Cite This Course

Course Description

Course Features

Course Description

This course provides an introductory survey of data science tools in healthcare. It was created by members of MIT Critical Data, a global consortium consisting of healthcare practitioners, computer scientists, and engineers from academia, industry, and government, that seeks to place data and research at the front and center of healthcare operations.

The most daunting global health issues right now are the result of interconnected crises. In this course, we highlight the importance of a multidisciplinary approach to health data science. It is intended for front-line clinicians and public health practitioners, as well as computer scientists, engineers, and social scientists, whose goal is to understand health and disease better using digital data captured in the process of care.

What you'll learn:

  • Principles of data science as applied to health
  • Analysis of electronic health records
  • Artificial intelligence and machine learning in healthcare

This course is part of the Open Learning Library, which is free to use. You have the option to sign up and enroll in the course if you want to track your progress, or you can view and use all the materials without enrolling.


Related Content

Leo Celi, Louis Agha-Mir-Salim, and Marie-Laure Charpignon. HST.953 Collaborative Data Science for Healthcare. Fall 2020. Massachusetts Institute of Technology: MIT OpenCourseWare, License: Creative Commons BY-NC-SA.

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