Applied Mathematics and Data Science, Master of Arts (M.A.)
Program Objectives
The objectives of the graduate mathematics program are the following:
- To provide a graduate program in mathematics and statistics leading to a degree which prepares students for careers in government or industry.
- To provide a graduate program in mathematics designed for certified high school teachers who wish to broaden their knowledge of the mathematics related to the field in which they teach.
- To provide the necessary mathematical content for certified teachers to teach dual-credit courses at the secondary level or courses at a community college, two-year college, or four-year college.
- To include in this program courses in the areas of mathematics, statistics, statistical analysis, mathematics applications, and courses demonstrating the relationships among these fields.
- To guide students in tailoring a program of study ideally suited to their background, aptitude, and career interests.
Admission Requirements
Clear admission to graduate standing will be granted to those students who have the following:
- An undergraduate grade point average of 2.5 or higher.
- Prerequisites for the core courses. (For example, six hours of calculus and courses in linear algebra and statistics would be sufficient.) Applicants who do not have this preparation may be granted admission without the prerequisites but are required to take the courses needed to strengthen their backgrounds. Students seeking a change in Kentucky Teacher rank must have initial certification in secondary mathematics.
Program Requirements
CIP Code: 27.0503
Applied Mathematics Program
Each student must apply 15 or more hours from 800-level courses toward the M.A. degree.
| Code | Title | Hours |
|---|---|---|
| Core Courses | ||
| MAT 720 | Mathematical Statistics I | 3 |
| or STA 720 | Mathematical Statistics I | |
| MAT 865 | Applied Linear Algebra | 3 |
| MAT 866 | Combinatorial Optimization | 3 |
| DSC 780 | R and Introductory Data Mining | 3 |
| or STA 780 | R and Introductory Data Mining | |
| MAT 898 | Applied Mathematics Capstone | 3 |
| Electives: Choose from fifteen hours of advisor-approved electives selected from 700- or 800-level courses with DSC, MAT, STA prefixes or: | 15 | |
| Theory of Database Systems | ||
| Artificial Intelligence | ||
| Machine Learning | ||
| Big Data | ||
| Data Visualization | ||
| Object-Oriented Programming | ||
| Total Hours | 30 | |