The Data Science MS degree with major in Mathematics requires 30 credit hours of coursework. There is a core curriculum of 18 credit hours all Data Science students take. In addition, students who major in Mathematics take at least 9 credit hours from mathematics. The rest of the credit hours can be taken from the participating departments.

Students interested in taking an elective class that is not listed here should contact Dr. Ökten.

All data science graduate students must pass the following courses:

Core Requirements: (18 credit hours)

• MAP 5196 - Mathematics for Data Science (3 Hrs, Fall)
• COP 5XXX - Introduction to Data Science (3 Hrs, Fall)
• STA 5207 - Applied Regression Methods (3 Hrs, Fall)
• XXX 5XXX - Professional Development Seminar (1 Hr, Fall)
• STA 5635 - Machine Learning (3 Hrs, Spring)
• CAP 5771 - Data Mining (3 Hrs, Spring)
• PHI 5XXX - Data Ethics (2 Hrs, Spring)

Math Major Requirements: (At least 9 credit hours)

• MAD 5XXX - Principles and Foundations of Machine Learning (3 Hrs, Fall)
• MAD 5XXX - Numerical Linear Algebra (3 hrs) Spring)
• MAD 5420 - Numerical Optimization (3 Hrs, Fall)
• MAD 5306 - Graphs and Networks (3 Hrs, Fall)
• MAD 5XXX - Topological Data Analysis (3 Hrs, Fall)

After satisfying the core and math major requirements, students who need additional credit hours can take more courses from the above list or the electives below:

• CAP 5XXX - Advanced Topics in Data Science (3 hrs)
• STA 5326 - Distribution Theory and Inference (3 hrs)
• STA 5166 - Statistics in Application I (3 hrs)
• STA 5167 - Statistics in Application II (3 hrs)
• MAD 5403 - Foundations of Computational Mathematics (3 hrs)
• MAD 5403 - Foundations of Computational Mathematics II (3 hrs)

A schedule to complete the degree in three semesters: