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