1. Master of Science in Biomedical Data Science
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The Master of Science in Biomedical Data Science Program at the Icahn School of Medicine at Mount Sinai is a 30-credit program, designed to be completed in 18-24 months, that hones your technical skills through rigorous training and independent research. By applying informatics to biomedical problems, you can uncover the missing pieces to today’s most pressing health challenges. Our curriculum is designed to energize your computational, mathematical, and statistical thinking to maximize the impact on human health and well-being.

Program Requirements

Our program integrates training and education in various aspects of biomedical sciences with machine learning, computer systems, and big data analysis.

Students can choose from the following two core options, depending on the focus for your capstone project:

  • Biomedical Sciences (six credits)
  • Principles of Neural Science, Behavior, and Brain Pathophysiology (six credits)

Students must take the following three required courses, totaling nine credits:

  • Computer Systems (three credits)
  • Introduction to Algorithms (three credits)
  • Machine Learning for Biomedical Data Science (three credits)

Students must take the following two additional mandatory training requisites:

  • Responsible Conduct of Research (Eight hours of training, half credit)
  • Rigor and Reproducibility (Eight hours of training, half credit)

Students must take two-and-a-half to five elective credits in order to do complementary coursework in areas of greatest interest to them. Elective options include:

  • Introduction to Biostatistics | three credits
  • Biostatistics for Biomedical Research | three credits
  • Analysis of Categorical Data | three credits
  • Theory of Linear and Generalized Linear Models | three credits
  • Applied Analysis of Health Care Databases | three credits
  • Biomedical Software Engineering | two credits
  • Applied Linear Models | three credits
  • Intro to Artificial Intelligence/Deep Learning in Biomedical Research | one credit
  • Introduction to R Programming | two credits
  • Programming in Systems Biomedicine | two credits
  • Analysis of Longitudinal Data | three credits
  • Applied Linear Models II (Prereq ALM 1) | three credits

For your capstone research project (BDS 9001), you may choose from one of the following biomedical data science research areas:

  • Computational genomics
  • Computational biophysics
  • Systems pharmacology
  • Biomedical engineering
  • Imaging and visualization
  • Biostatistics
  • Clinical epidemiology
  • Clinical trials
  • Environmental medicine
  • Public health
  • Health systems design
  • Health information technology

Extract Health Insights From Robust Data

MS in Biomedical Data Science Program
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