- Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
- Certain options within the program may be required at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality.
Complete all courses and requirements listed below unless otherwise indicated.
Core Requirements
| Code | Title | Hours |
|---|---|---|
| Modeling | ||
| Complete 4 semester hours from the following: | ||
| Applied Linear Algebra and Matrix Analysis | ||
| Introduction to Mathematical Methods and Modeling | ||
| Numerical Analysis 1 | ||
| Graph Theory | ||
| Probability 1 | ||
| Statistics | ||
| Complete 4 semester hours from the following: | ||
| Machine Learning and Statistical Learning Theory 1 | ||
| Applied Statistics | ||
Electives
| Code | Title | Hours |
|---|---|---|
| Complete 8 semester hours from subject area MATH, including but not limited to the following: | ||
| Analysis 1: Functions of One Variable | ||
| Algebra 1 | ||
| Topology 1 | ||
| Partial Differential Equations 1 | ||
| Numerical Analysis 2 | ||
| Riemannian Optimization | ||
| Optimization and Complexity | ||
| Machine Learning and Statistical Learning Theory 2 | ||
| Probability 2 | ||
| Mathematical Statistics | ||
| Applied Statistics | ||
| Regression, ANOVA, and Design | ||
Program Credit/GPA Requirements
16 total semester hours required
Minimum 3.000 GPA required