About MS Track of Data Science in Biomedicine

There is a new track within the Computer Science MS degree program focusing on Data Science with applications in Biomedicine.
We offer this new track in response to the prominence of the fourth paradigm of scientific discovery, dubbed data science, which seeks to exploit information buried in massive data sets to drive discovery. Data science has emerged as an essential complement to the three other existing paradigms, i.e., theory, experimentation, and scientific computing, with a widespread and growing set of applications in almost all disciplines, including biomedicine, health informatics, precision and personalized medicine, business analytics, intelligent transportation, and cybersecurity, to name a few. With the new track, students pursuing this training within the Computer Science MS program will particularly adopt biomedical applications of data science (as a sample data science application domain) to learn data science methodologies and technologies. Upon successful graduation from the Computer Science MS program under the “Data Science in Biomedicine” track, students will have an official designation of data science training within their degree, which will help with employment and other opportunities.


MS students and PhD students who are in the process of obtaining a MS degree are eligible. It is best to plan out the track starting the first year to ensure timely graduation and availability of electives.


  • • 36 credits total
  • • Take 9 credits of electives from a list of courses related to Biomedical Computing and Informatics, Bioinformatics, Health Informatics, etc.
  • • Select your other electives among CS courses focused on data science and engineering, to specialize your MS studies on data science as compared to the original MS degree.
  • • Write a thesis with a focus on Data Science in Biomedicine.

The complete curriculum of the Data Science in Biomedicine track of the CS MS program is available here.


Sarah Mandos


Program Assistant II
Computer Science and Engineering Department
University of Colorado Denver
Phone: (303)-315-1411
Email: sarah.mandos@ucdenver.edu