Foundations of Data Science (MS): Mathematics Concentration
Degree Requirements
| Code | Title | Hours | Counts towards |
|---|---|---|---|
| Required Courses | 21 | ||
Statistics Core | |||
| Fundamentals of Linear Models and Regression | |||
| Applied Statistical Methods I | |||
Mathematics Core | |||
| Linear Transformations and Matrix Theory | |||
| Convex Optimization Methods in Data Science | |||
Computer Science core | |||
| Design and Analysis Of Algorithms | |||
| Database Management Concepts and Systems | |||
Machine Learning core (choose one of the following) | |||
| Introduction to Statistical Learning | |||
| Automated Learning and Data Analysis | |||
| Concentration Electives | 9 | ||
| A minimum of 9 hours of elective courses must be taken from the following courses: | |||
| Uncertainty Quantification for Physical and Biological Models | |||
| Numerical Analysis I | |||
| Numerical Methods for Nonlinear Equations and Optimization | |||
| Special Topics In Numerical Analysis | |||
| Total Hours | 30 | ||