Academic Programs Catalog

College of Natural Science

Department of Computational Mathematics, Science and Engineering

Edward Brown, Chairperson

Computational Mathematics, Science and Engineering is the multidisciplinary field that is concerned with the use of advanced computing capabilities to solve complex problems pertaining to computational modeling and data science.  Among the areas of interest include the development and analysis of algorithms, high performance computing, including both parallel computing and heterogeneous architectures, and the application of both algorithms and high performance computing to modeling and data analysis, exploration, and visualization.  The department offers a wide range of courses in computational and data science.  Graduates will use their skills in large-scale computing and data science to address a wide variety of problems in science, engineering, and other fields.

The Department of Computational Mathematics, Science and Engineering is administered jointly by the colleges of Natural Science, and Engineering.

 

Undergraduate Programs


Data Science

The Bachelor of Science degree 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.

Requirements for the Bachelor of Science Degree in Data Science

  1. The University requirements for bachelor's degrees as described in the Undergraduate Education section of this catalog; 120 credits, including general elective credits, are required for the Bachelor of Science degree in Data Science.
    The University's Tier II writing requirement for the Data Science major is met by completing Computational Mathematics, Science and Engineering 495, referenced in item 3. below.
  2. The requirements of the College of Natural Science for the Bachelor of Science degree.
    1. The following requirements for the major:
      a. One course from each of the following groups (8 or 10 credits):
      (1) CEM 141 General Chemistry 4
      CEM 151 General and Descriptive Chemistry 4
      CEM 181H Honors Chemistry I 4
      LB 171 Principles of Chemistry I 4
      (2) CEM 142 General and Inorganic Chemistry 3
      CEM 152 Principles of Chemistry 3
      CEM 182H Honors Chemistry II 4
      LB 172 Principles of Chemistry II 3
      (3) CEM 161 Chemistry Laboratory I 1
      CEM 185H Honors Chemistry Laboratory I 2
      LB 171L Introductory Chemistry Laboratory I 1
      b. One course from each of the following groups (8 to 10 credits):
      (1) LB 273 Physics I 4
      PHY 173 Studio Physics for Scientists and Engineers I 5
      PHY 183 Physics for Scientists and Engineers I 4
      (2) LB 274 Physics II 4
      PHY 174 Studio Physics for Scientists and Engineers II 5
      PHY 184 Physics for Scientists and Engineers II 4
      c. One course from each of the following groups (14 or 15 credits):
      (1) LB 118 Calculus I 4
      MTH 132 Calculus I 3
      MTH 152H Honors Calculus I 3
      (2) LB 119 Calculus II 4
      MTH 133 Calculus II 4
      MTH 153H Honors Calculus II 4
      (3) LB 220 Calculus III 4
      MTH 234 Multivariable Calculus 4
      MTH 254H Honors Multivariable Calculus 4
      (4) MTH 314 Matrix Algebra with Computational Applications 3
      d. One of the following groups (4 or 6 credits):
      (1) STT 380 Probability and Statistics for Data Science 4
      (2) STT 441 Probability and Statistics I: Probability 3
      STT 442 Probability and Statistics I: Statistics 3
      e. All of the following courses (31 credits):
      CMSE 201 Introduction to Computational Modeling and Data Analysis 4
      CMSE 202 Computational Modeling Tools and Techniques 4
      CMSE 381 Fundamentals of Data Science Methods 4
      CMSE 382 Optimization Methods in Data Science 4
      CMSE 495 Experiential Learning in Data Science 4
      CSE 232 Introduction to Programming II 4
      CSE 331 Algorithms and Data Structures 3
      STT 180 Introduction to Data Science 4
      f. A minimum of 12 credits of approved 400-level courses or above. The following courses are eligible to fulfill this requirement. Other may be substituted with advisor approval.
      CMSE 401 Methods for Parallel Computing 4
      CMSE 402 Data Visualization Principles and Techniques 3
      CMSE 410 Computational Biology and Bioinformatics 3
      CMSE 411 Computational Medicine 3
      CMSE 492 Special Topics in Data Science 1 to 4
      CSE 402 Biometrics and Pattern Recognition 3
      CSE 404 Introduction to Machine Learning 3
      CSE 440 Introduction to Artificial Intelligence 3
      CSE 480 Database Systems 3
      CSE 482 Big Data Analysis 3
      MTH 468 Predictive Analytics 3
      STT 464 Statistics for Biologists 3
      STT 465 Bayesian Statistical Methods 3
      A maximum of 12 credits may count towards the degree for enrollments in CMSE 492 with advisor approval.

 

Minor in Computational Mathematics, Science, and Engineering

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: 

1. Both of the following courses (8 credits):
CMSE 201 Computational Modeling and Data Analysis I 4
CMSE 202 Computational Modeling and Data Analysis II 4
2. Complete a minimum of 9 credits from the following courses:
CMSE 401 Methods for Parallel Computing 4
CMSE 410 Bioinformatics and Computational Biology 3
CMSE 411 Computational Medcine 3
CMSE 402 Visualization of Scientific Datasets 3
CSE 232 Introduction to Programming II 4
CSE 404 Introduction to Machine Learning 3
CSE 415 Introduction to Parallel Computing 3
CSE 482 Big Data Analysis 3
MTH 314 Matrix Algebra with Computational Applications
MTH 451 Numerical Analysis I 3
MTH 452 Numerical Analysis II 3
PHY 480 Computational Physics 3
PLB 400 Introduction to Bioinformatics 3
STT 461 Computations in Probability and Statistics 3
STT 465 Bayesian Statistical Methods 3
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.



 

Minor in Data Science

The Minor in Data Science, which is administered by the Department of Computational Mathematics, Science, and Engineering, 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.

The minor is available as an elective to students 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 apply to the program should consult the undergraduate advisor in the Department of Computational Mathematics, Science, and Engineering.

Requirements for the Minor in Data Science

Complete a minimum of 23 credits from the following:

1. All of the following courses (19 credits):
CMSE 201 Introduction to Computational Modeling and Data Analysis 4
CMSE 202 Computational Modeling Tools and Techniques 4
CMSE 381 Fundamentals of Data Science Methods 4
MTH 314 Matrix Algebra with Computational Applications 3
STT 180 Introduction to Data Science 4
2. One of the following groups (4 or 6 credits):
a. STT 380 Probability and Statistics for Data Science 4
b. STT 441 Probability and Statistics I: Probability 3
STT 442 Probability and Statistics I: Statistics 3



 

Graduate Study

The Department of Computational Mathematics, Science and Engineering offers the programs listed below:

    Master of Science
        Computational Mathematics, Science and Engineering
    Doctor of Philosophy
        Computational Mathematics, Science and Engineering
    Graduate Certificate
        Computational Modeling
        High-Performance Computing

Study for the department's graduate degree programs is administered by the College of Engineering.