Master of Science in Biomedical Data Science and Modeling

The overall objective of the Master of Science in Biomedical Data Science and Modeling is to provide education and training relevant to professional employment in computational biomedical engineering. Special emphasis is placed on principles of mathematical modeling, machine learning, biostatistics, and bioinformatics. The student must have a minimum 3.0/4.0 GPA in an engineering or science bachelor’s program to be admitted. Candidates should have prior coursework that demonstrates proficiency in math and computer science. 



Minimum Credits Required 32
Maximum 400-Level Credit 12
Minimum 500-Level Credit 20
Maximum Transfer Credit 9
Required Courses (20)
BIOL 550Bioinformatics3
BME 500Introduction to Biomedical Engineering (In Fall 2021, we will change credit hours of BME 500 from 3 to 2)2
BME 522Mathematical Methods in Biomedical Engineering3
or BME 422 Mathematical Methods for Biomedical Engineers
or CHE 439 Numerical and Data Analysis
or CHE 535 Applications of Mathematics to Chemical Engineering
BME 533Biostatistics3
or BME 433 Biomedical Engineering Applications of Statistics
or CHE 426 Statistical Tools for Engineers
or MATH 425 Statistical Methods
or MATH 476 Statistics
BME 553Advanced Quantitative Physiology3
or BME 453 Quantitative Physiology
BME 560Methods in Biomedical Data Science3
ECE 566Machine and Deep Learning3
Elective Courses (12)
Select 2 courses from the following list (6 credits) plus an additional 6 credits of Math/Life Science/Eng courses recommended from this list. Other courses may be selected with adviser approval prior to course registration.12
Genetics for Engineering Scientists3
Population Genetics3
Introduction to Molecular Imaging3
Reaction Kinetics for Biomedical Engineering3
Quantitative Neural Function3
Advanced Mass Transport for Biomedical Engineers3
Special Problems1-6
Advanced Data Mining3
Deep Learning3
Interactive and Transparent Machine Learning3
Machine Learning3
Applied Optimization for Engineers3
Statistical Signal Processing3
Mathematical Modeling (or)3
Statistical Learning (or)3
Data Preparation and Analysis (or)3
Computational Mathematics I (or)3
Finite Element Methods in Engineering3
Engineering Analysis I3
Engineering Analysis II3
Computational Fluid Dynamics3
Applied Computational Statistics for Analytics3
Total Credit Hours32