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.
The core required courses for the degree are:
- CSE 8423 - Data Science: Concepts & Practice
- ST 8123 - Statistical Thinking
- ST 8133 - Statistical Modeling
- CSE 6503 - Database Management Systems
- CSE 8080 - Directed Project in Computer Science
The additional 15 hours of coursework can be chosen from the following:
- 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
- Approved - CSE 8990 or ST 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:
- Graduate Coordinator - Co-coordinator: Dr. T.J. Jankun-Kelly firstname.lastname@example.org
- Graduate Coordinator - Co-coordinator: Dr. Mohammad Sepehrifar email@example.com