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 |