Minor in Data Science
The Minor in Data Science is designed to provide students with a strong background in data science using a broad range of computational techniques, practice in statistical thinking, as well as in-depth exposure to topics in data science.
Students who plan to complete the requirements of the minor should consult the undergraduate advisor in CMSE (email@example.com)
Complete a minimum of 23 credits from the following:
- Requirements (19 credits):
- STT 180 Introduction to Data Science (4 credits)
- CMSE 201 Introduction to Computational Modeling and Data Analysis (4 credits)
- CMSE 202 Computational Modeling Tools and Techniques (4 credits)
- CMSE 381 Fundamentals of Data Science Methods (4 credits)
- MTH 314 Matrix Algebra with Computational Applications (3 credits)
- One of the Following groups (4 or 6 credits):
- STT 380 Probability and Statistics for Data Science (4 credits)
- STT 441 Probability and Statistics I: Probability (3 credits)
- STT 332 Probability and Statistics I: Statistics (3 credits)
Grade and GPA requirements
As per the university GPA and minimum grade requirements:
- You must achieve a minimum recorded GPA of 2.0 in all courses contributing to the CMSE Minor in order to receive the minor.
- You must achieve a minimum grade of 1.0 for all courses contributing to the CMSE minor in order to receive the minor.