Undergraduate Degree - Computational Data Science

Program:
Computational Data Science
Program Code:
8096 Computational Data Science
Program Level:
Undergraduate
Award Type:
Bachelor of Science
Start Term:
FS19


Excerpt from the official Academic Programs Catalog:

Listed below are the approved requirements for the program from the official Academic Programs Catalog.
Students must consult their advisors to learn which specific requirements apply to their degree programs.
Following this section are the requirements as represented in Degree Navigator, MSU's online advising tool. The Degree Navigator section is only available for programs using Degree Navigator for degree certification.

College of Engineering

Department of Computer Science and Engineering

Undergraduate Programs
Computational Data Science

The Bachelor of Science degree in Computational Data Science focuses on the computational foundations of data science, providing an in-depth understanding of the algorithms and data structures for storing, manipulating, visualizing, and learning from large data sets. Students in the program have unique access to a wide range of fundamental computer science courses in topics ranging from mobile application and web development to theory of computation and fundamental algorithms. Students can tailor their degree to their unique interests and requirements, with an emphasis on computational foundations.

Requirements for the Bachelor of Science Degree in Computational 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 Computational Data Science.

    The University's Tier II writing requirement for the Computational Data Science major is met by completing Computational Mathematics, Science and Engineering 495, referenced in item 3. b. below.

    Students who are enrolled in the College of Engineering may complete the alternative track to Integrative Studies in Biological and Physical Sciences that is described in item 1. under the heading Graduation Requirements for All Majors in the College statement.
  2. The requirements of the College of Engineering for the Bachelor of Science degree.

    The credits earned in certain courses referenced in requirement 3. below may be counted toward College requirements as appropriate.
  3. The following requirements for the major:
    a. Bioscience (4 to 6 credits)
    (1) One of the following courses:
    BS   161 Cell and Molecular Biology  3
       ENT  205 Pests, Society and Environment  3
    IBIO   150 Integrating Biology: From DNA to Populations  3
          MMG  141 Introductory Human Genetics  3
          MMG   201 Fundamentals of Microbiology  3
          PLB   105 Plant Biology  3
          PSL  250 Introductory Physiology  4
    (2) One of the following courses:
    BS  171 Cell and Molecular Biology Laboratory  2
          CEM  161 Chemistry Laboratory I  1
          CEM  162 Chemistry Laboratory II  1
          PHY  191 Physics Laboratory for Scientists, I  1
          PHY  192 Physics Laboratory for Scientists, II  1
          PLB  106 Plant Biology Laboratory 1
    b.  All of the following courses (44 credits):
    CMSE  201 Introduction to Computational Modeling and Data Analysis 4
       CMSE  381 Fundamentals of Data Science Methods  4
       CMSE  382 Optimization Methods in Data Science  4
       CMSE  495 Experiential Learning in Data Science (W) 4
    CSE  232 Introduction to Programming II  4
    CSE 300 Social, Ethical, and Professional Issues in Computer Science 1
       CSE  331 Algorithms and Data Structures  3
       CSE  404 Introduction to Machine Learning  3
       CSE  482 Big Data Analysis  3
       CSE  480 Database Systems  3
    MTH  314 Matrix Algebra with Computational Applications 3
    STT  180 Introduction to Data Science  4
       STT  380 Probability and Statistics for Data Science  4
    c.  Two courses selected from the following (6 credits): 
    CSE  402 Biometrics and Pattern Recognition  3
       CSE  415 Introduction to Parallel Computing  3
       CSE  431 Algorithm Engineering  3
       CSE  440 Introduction to Artificial Intelligence  3
    Computer Science and Engineering 415 and Computational Science, Mathematics and Engineering 401 may not be used to fulfill both requirements c. and d.
    d.  Two courses selected from the following (6 credits):
    CMSE  401 Methods for Parallel Computing  4
       CMSE  402 Data Visualization Principles and Techniques 3
    CSE  402 Biometrics and Pattern Recognition  3
       CSE  415 Introduction to Parallel Computing  3
       CSE  431 Algorithm Engineering  3
       CSE  440 Introduction to Artificial Intelligence  3
       CSE  471 Media Processing and Multimedia Computing  3
       CSE  472 Computer Graphics  3
       MTH  451 Numerical Analysis I  3
       MTH  468 Predictive Analytics 3
       STT  464 Statistics for Biologists  3
       STT  465 Bayesian Statistical Methods  3
    Computer Science and Engineering 415 and Computational Science, Mathematics and Engineering 401 may not be used to fulfill both requirements c. and d.