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. 

 

Curriculum

Requirement
Minimum Credits Required 32
Maximum 400-Level Credit 9
Minimum 500-Level Credit 23
Maximum Transfer Credit 9
Required Courses (20-21)
BME 500Intro to Biomedical Engrg (In Fall 2020, we will change credit hours of BME 500 from 3 to 2)2-3
BME 533Biostatistics3
or BME 433 BME Applications of Statistics
BME 553Quantitative Physiology3
BME 560Methods in Biomedical Data Sci3
BME 522Math Methods in BME3
or BME 422 Math Methods for Boimdel Engrs
BIOL 550Bioinformatics3
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
Deep Learning (or)3
Online Social Network Analysis (or)3
Mathematical Modeling (or)3
Statistical Learning (or)3
Data Preparation and Analysis (or)3
Computational Mathematics I (or)3
Total Credit Hours32-33