Foundations of Data Science (MS): Mathematics Concentration
Degree Requirements
| Code | Title | Hours |
|---|---|---|
| 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 | ||
| Computational Methods for Variational Inverse Problems | ||
| Numerical Methods for Nonlinear Equations and Optimization | ||
| Total Hours | 30 | |