The Minor in Computational Mathematics, Science, and Engineering complements a students’ major by providing a strong background in computational modeling of a variety of systems using a broad range of computational techniques, 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 exception of the Bachelor of Science Degree in Data Science and the Bachelor of Science Degree in Computational Data Science. 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 consult the undergraduate advisor in the Department of Computational Mathematics, Science, and Engineering.
Requirements for the Minor in Computational Mathematics, Science, and Engineering
Complete 17 credits from the following:
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| 1. |
Both of the following courses (8 credits): |
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CMSE |
201 |
Computational Modeling and Data Analysis I |
4 |
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CMSE |
202 |
Computational Modeling and Data Analysis II |
4 |
| 2. |
Complete a minimum of 9 credits from the following courses: |
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CMSE |
401 |
Methods for Parallel Computing |
4 |
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CMSE |
410 |
Bioinformatics and Computational Biology |
3 |
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CMSE |
411 |
Computational Medcine |
3 |
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CMSE |
402 |
Visualization of Scientific Datasets |
3 |
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CSE |
232 |
Introduction to Programming II |
4 |
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CSE |
404 |
Introduction to Machine Learning |
3 |
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CSE |
415 |
Introduction to Parallel Computing |
3 |
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CSE |
482 |
Big Data Analysis |
3 |
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MTH |
314 |
Matrix Algebra with Computational Applications |
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MTH |
451 |
Numerical Analysis I |
3 |
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MTH |
452 |
Numerical Analysis II |
3 |
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PHY |
480 |
Computational Physics |
3 |
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PLB |
400 |
Introduction to Bioinformatics |
3 |
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STT |
461 |
Computations in Probability and Statistics |
3 |
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STT |
465 |
Bayesian Statistical Methods |
3 |
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Additional courses may be used with approval of the program advisor including additional CMSE 300-400 level courses. Courses outside of CMSE with a strong focus on the applications of computational methods or on discipline-related computational techniques will be considered. |