Sample M.S. schedules

To see how your classes in the data science program might look, check out the sample schedules below.  The schedules below are simply examples, and are not required.  Students are welcome to take courses at their own pace, meaning that may complete the degree beyond 4 semesters if needed. 

3 semester option

Semester 1
Course Title Credits
CSCI 5523 - Introduction to Data Mining 3
CSCI 5707 - Principles of Database Systems 3
STAT 5302 - Applied Regression Analysis 4
Colloquium 1
Elective 3
Total Credits 14
Semester 2
Course Title Credits
CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming 3
EE 5239 - Introduction to Nonlinear Optimization 3
STAT 5401 - Applied Multivariate Methods 3
Elective (8000 level) 3
Total Credits 12
Semester 3
Course Title Credits
Elective 3
Capstone Project 3
Total Credits 6

4 semester option

Semester 1
Course Title Credits
CSCI 5523 - Introduction to Data Mining 3
CSCI 5707 - Principles of Database Systems 3
STAT 5302 - Applied Regression Analysis 4
Colloquium (1cr) 1
Total Credits 11
Semester 2
Course Title Credits
CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming 3
EE 5239 - Introduction to Nonlinear Optimization 3
STAT 5401 - Applied Multivariate Methods 3
Total Credits 9
Semester 3
Course Title Credits
Elective 3
Elective (8000 level) 3
Total Credits 6
Semester 4
Course Title Credits
Elective 3
Capstone Project 3
Total Credits 6

Questions?

Allison Small headshot

Allison Small

Graduate Program Coordinator

Current students: [email protected]
Prospective students: [email protected]