Academics / Graduate Study / Special ProgramsMS Concentration in Data Science
The Biomedical Engineering MS Concentration in Data Science provides an opportunity to develop a general foundation in data science and the opportunity to build skills in subfields of the discipline. Students who complete the Data Science concentration better equipped to develop comprehensive data science pipelines, using computational data analysis for the estimation, prediction, design, and control of engineering systems.
Choose 3 that contribute to MS degree requirements. (These are not separate from the MS degree.)
Programming and Statistics
| Course Number | Course Title |
|---|---|
| BMD_ENG 407 | Experimental Design and Measurement |
| COMP_SCI 330 | Human Computer Interaction |
| COMP_SCI 339 | Introduction to Databases |
| COMP_SCI 349 | Machine Learning |
| COMP_ENG 465 | Internet-of-things Sensors, Systems and Applications |
| COMP_ENG 466 | Embedded Systems |
| ELEC_ENG 332 | Introduction to Computer Vision |
| ELEC_ENG 395, 495 | Optimization Techniques for Machine Learning and Deep Learning |
| ELEC_ENG 475 | Machine Learning: Foundations, Applications, and Algorithms |
| IEMS 304 | Statistical Learning for Data Analysis |
| IEMS 310 | Operations Research |
| IEMS 313 | Foundations of Optimization |
| IEMS 450 | Mathematical Optimization I |
Machine Learning and Data Science Electives
| Course Number | Course Title |
|---|---|
| BMD_ENG 311-0 | Computational Genomics |
| BMD_ENG 312-0 | Biomedical Applications in Machine Learning |
| CHEM_ENG 379-0 | Computational Biology: Analysis and Design of Living Systems |
| COMP_SCI 348-0 | Introduction to Artificial Intelligence |
| COMP_SCI 449-0 | Deep Learning |
| COMP_SCI 496-0 | Special Topics in Computer Science (Visualization for Scientific Communication) |
| ELEC_ENG 473-0 | Deep Reinforcement Learning from Scratch |
| ELEC_ENG 433-0 | Statistical Pattern Recognition |
| ELEC_ENG 435-0 | Deep Learning Foundations from Scratch |
| ES_APPM 345-0 | Applied Linear Algebra |
| ES_APPM 472-0 | Introduction to the Analysis of RNA Sequencing Data |
| MECH_ENG 441-0 | Engineering Optimization for Product Design and Manufacturing |
| MECH_ENG 469-0 | Machine Learning and Artificial Intelligence for Robotics |
| MECH_ENG 495-0 | Selected Topics in Mechanical Engg (Sensing Navigation and Machine Learning for Robotics) |
FAQ
Q: Am I able to take courses that are not part of the Graduate School as part of this concentration?
A: MS without thesis students are required to take a total of 12 courses to fulfill MS degree requirements. Nine of the 12 must be part of the Graduate School (TGS) career track; therefore, MS Course-Only students who follow the Translational Concentration are able to take up to 3 courses outside of the Graduate School. All plans of study must be approved by the Director of the MS Program prior to enrolling in the courses. MS Thesis students are required to take 9 courses to fulfill MS degree requirements; therefore, all three courses for the Translational Concentration must be part of TGS course career or students will be required to take additional TGS courses to fulfill the MS degree requirements.