Degree Requirement
Students are required to complete a minimum of thirty-two (32) units of course work. For course descriptions, please use the “Courses of Instruction” search tool on the Catalogue.
At least 32 units are required, including:
Core Curriculum (5 courses, 19 units)
| COURSE | COURSE TITLE | UNITS |
| MATH 447 | Mathematics of Machine Learning | 4 |
| MATH 546 | Mathematical Statistics for Data Science | 4 |
| MATH 549 | Foundations of Mathematical Data Science | 4 |
| MATH 550 | Statistical Consulting and Data Analysis | 3 |
| PHYS 515 | Python for Data Science and Scientific Computing | 4 |
Electives (12 units, selected from the following list)
| COURSE | COURSE TITLE | UNITS |
| MATH 446 | Data Science with Python | 4 |
| MATH 505a | Applied Probability | 3 |
| MATH 542 | Analysis of Variance and Design | 3 |
| MATH 545 | Introduction to Time Series | 3 |
| MATH 547 | Mathematical Foundations of Statistical Learning Theory | 3 |
| MATH 548 | Machine Learning in Quantitative Finance | 3 |
| ISE 530 | Optimization Methods for Analytics | 4 |
Additional Requirements
To complete the program, students enroll in at least 1 unit of MATH 590 Directed Research and submit a summative report at the end of the term. Note: enrollment in MATH 590 will often be concurrent with enrollment in MATH 550. Students should consult with their advisor for details.