M.S. in Data Science

M.S. in Data Science

The interdisciplinary Master of Science in Data Science degree program will provide students with broad training in managing, processing, and extracting value from large and diverse data sets and allow them to communicate their findings. The program will prepare students for professional employment in industry, government, and NGOs and at the same time allow them to obtain sufficient skills to continue into more advanced degree programs.

Admission to the Master's program in Data Science is open to graduates from all disciplines with a strong quantitative background and computational skills. The program of study is a blend of statistical and optimization methodologies laced with data management and computational skills, and it provides graduate students with the opportunity to participate in data analytics projects.

Upon completion of the MS in Data Science, students will be able to:

  • Demonstrate a depth and breadth in understand statistical modeling, data management, and extracting meaning from data.
  • Communicate effectively to a broad range of audiences, demonstrating research capability and data science application.

This degree is a 30 credit, courses-only Master's degree, that requires programming and mathematics as pre-requisites (including Data Structures, Calculus II, and Linear Algebra). The degree requires a final, project-based capstone to put the data science knowledge into practice, and will include a written and oral report evaluated by the student’s committee. As this is a joint program between the Department of Mathematics and Statistics and the Department of Computer Science and Engineering, supervision and advising will be shared among both departments.

Degree Core (12 Hours)

  • CSE 8423 Data Science Concepts and Practice
  • ST 8123 Statistical Thinking: Probability Models and Theory of Statistics
  • ST 8133 Statistical Modeling
  • CSE 6503 Database Management Systems

General Concentration

  • Graduate Data Science Electives (15 hours)

Manufacturing Analytics Concentration

  • IE 6673 Reliability Engineering
  • IE 6683 Machine Learning with Industrial Engineering Applications
  • IE 8623 Advanced Data Analytics for Complex Systems
  • Graduate Data Science Electives (6 hours)

Geospatial Science Concentration

  • GR 6303 Principles of GIS
  • GR 6313 Advanced GIS
  • GR 6333 Remote Sensing of the Physical Environment
  • Graduate Data Science Electives (6 hours), including the following:
    • GR 6343 Advanced Remote Sensing
    • GR 6353 Geodatabase Systems
    • GR 6363 Geographic Information Systems Programming
    • GR 8453 Quantitative Methods in Climatology

Agricultural Autonomy Concentration

  • ABE 6463 Introduction to Imaging in Biological Systems
  • ABE 6900 Robotics for Biological Systems
  • CSE 6643 AI Robotics
  • Concentration Elective(s) (3 or 6 hours)
    • ABE 6483 Introduction to Remote Sensing Technologies
    • ABE 6433 Geospatial Computing for Biological Systems
    • ABE 6443 Spectroscopic Sensing in Biological Systems
  • Graduate Data Science Electives (0 or 3 hours)

Capstone (3 hours)

  • A committee approved capstone project course, such as a DIS or CSE 8080 Directed Project.

Electives Available

  • CSE 6433 Artificial Intelligence
  • CSE 6833 Introduction to Algorithms
  • CSE 8443 Visualization
  • CSE 8673 Machine Learning
  • CSE 8833 Algorithms
  • CSE 9633 Topics in AI
  • ST 8263 Advanced Regression Analysis
  • ST 8353 Statistical Computing
  • ST 8413 Multivariate Statistical Methods
  • ST 8214 Design and Analysis of Experiments
  • ABE 6433 Geospatial Computing for Biological Systems
  • ABE 6443 Spectroscopic Sensing in Biological Systems
  • IE 6934 Information Systems for Industrial Engineering
  • IE 8743 Nonlinear Programming
  • IE 8793 Heuristics in Optimization
  • IE 6623 Engineering Statistics II
  • IE 8333 Production Control Systems II
  • IE 8353 Manufacturing Systems Modeling
  • Approved CSE 6990/8990 or ST 6990/8990 Special Topics

The deadline for applications follows MSU guidelines (Deadlines | The Graduate School - Mississippi State University), and though funding is not guaranteed, students can apply through either the Department of Mathematics or Computer Science.

For further information, please contact one of the program coordinators: