MS in Mathematical Data Science
Admission
Students will be admitted to full graduate standing in the mathematical data science program if they have the equivalent of an undergraduate major in mathematics, have a grade point average of at least 3.000 in mathematics and computer sciences courses, and meet Graduate School admission requirements. Students may be admitted on a conditional basis if they do not have all the prerequisite coursework.
Program Requirements
To complete the MS in mathematical data science degree, students must earn 30 credit hours from the following list of courses:
| Course | Title | Hours |
|---|---|---|
| Six Required Courses | ||
| MATH 746 | Introduction to Data Analytics | 3 |
| BSAN 775 | Introduction to Business Analytics | 3 |
| CS 746 | Perspectives on Data Science | 3 |
| CS 770 | Machine Learning | 3 |
| MATH 553 | Mathematical Models | 3 |
| or MATH 657 | Optimization Theory | |
| MATH 802 | Data Analytics Capstone | 3 |
| Statistical Electives | ||
| Select two of the following courses | 6 | |
| Applied Regression Analysis | ||
| Analysis of Variance | ||
| Applied Statistical Methods I | ||
| Applied Statistical Methods II | ||
| Computing Elective | ||
| Select one of the following courses | 3 | |
| Statistical Computing I | ||
| Numerical Linear Algebra | ||
| Computational Methods for Physics | ||
| Design and Analysis of Algorithms | ||
| Other Elective | ||
| Select one of the following courses | 3 | |
| Matrix Theory | ||
| Introduction to Database Systems | ||
| Database Management Systems | ||
| Big Data Analytics in Engineering | ||
| Advanced Business Analytics | ||
| Total Credit Hours | 30 | |
Applied Learning
Students in the MS in mathematical data science are required to complete an applied learning or research experience to graduate from the program. The requirement can be met by taking MATH 802 Data Analytics Capstone.