Minor in CMSE
The Minor in Computational Mathematics, Science, and Engineering complements a student's major by providing a strong background in computational modeling of a variety of systems using a broad range of computational techniques, data analysis and visualization, functional and object-oriented computer programming, practice in computational thinking, as well as in-depth exposure to some subset of discipline-focused or methodology-focused topics in computational and/or data science.
The minor is available as an elective to students who are enrolled in bachelor’s degree programs at Michigan State University. With the approval of the department and college that administer the student’s degree program, the courses that are used to satisfy the minor may also be used to satisfy the requirements for the bachelor’s degree.
Students who plan to complete the requirements of the minor should contact the CMSE Undergraduate Director to request that the minor be added to their Student Profile. Please make sure to include in this request your MSU netid!
As described in the Academic Programs Catalog, students pursuing the Minor in Computational Mathematics, Science and Engineering must complete a minimum of 17 credits from the following two categories:
- Both of the following courses (8 credits):
- CMSE 201, Introduction to Computational Modeling (4 credits)
- CMSE 202, Computational Modeling Tools and Techniques (4 credits)
- A minimum of 9 credits from the following courses:
- CEM 481, Seminar in Computational Chemistry (3 credits)
- CMSE 401, Methods for Parallel Computing (4 credits)
- CMSE 402, Visualization of Scientific Datasets (3 credits)
- CSE 232, Introduction to Programming II (4 credits)
- MTH 314, Matrix Algebra with Computational Applications (3 credits)
- MTH 451, Numerical Analysis I (3 credits)
- MTH 452, Numerical Analysis II (3 credits)
- PHY 480, Computational Physics (3 credits)
- PLB 400, Introduction to Bioinformatics (3 credits)
- STT 180, Introduction to Data Science (4 credits) [Formerly STT 301]
- STT 301, Computational Methods for Data Science (3 credits) [Now STT 180]
- STT 461, Computations in Probability and Statistics (3 credits)
- STT 465, Bayesian Statistical Methods (3 credits)
Additional courses may be used with approval of the CMSE Undergraduate Director. Any CMSE 300-400 level courses including special topics and independent study courses will receive automatic approval. Courses outside of CMSE with a strong focus on the applications of computational methods or on discipline-related computational techniques will be considered, but only with approval from the CMSE Undergraduate Director prior to having taken the course in question.
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.