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

Tuition & Fees

Tuition per credit hour $558.50
Instructional Support Fee per credit hour $25.00

Tuition and fees listed are subject to change and do not include all possible charges. Additional fees may apply. Please refer to the master class schedule for individual course charges.

Program Structure

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)

Course Number Title Credit Hours
CSE 8423 Data Science: Concepts & Practice 3
ST 8123 Statistical Thinking 3
ST 8133 Statistical Modeling 3
CSE 6503 Database Management Systems 3
CSE 8080 Directed Project in Computer Science 3


General Concentration

Course Number Title Credit Hours
  General Data Science Electives (see listing below) 15


Manufacturing Analytics Concentration

Course Number Title Credit Hours
IE 6673 Reliability Engineering 3
IE 6683 Machine Learning with Industrial Engineering Applications 3
IE 8623 Advanced Data Analytics for Complex Systems 3
  Graduate Data Science Electives 6


Geospatial Science Concentration

Course Number Title Credit Hours
GR 6303 Principles of GIS 3
GR 6313 Advanced GIS 3
GR 6333 Remote Sensing of the Physical Environment 3
  Graduate Data Science Electives (choose from below) 6
GR 6343 Advanced Remote Sensing 3
GR 6353 Geodatabase Systems 3
GR 6363 Geographic Information Systems Programming 3
GR 8453 Quantitative Methods in Climatology 3


Agricultural Autonomy Concentration

Course Number Title Credit Hours
ABE 6463 Introduction to Imagining Biological Systems 3
ABE 6900 Robotics for Biological Systems 3
CSE 6643 AI Robotics 3
  Concentration Elective(s) - Choose from options below 3-6
ABE 6483 Introduction to Remote Sensing Technologies 3
ABE 6433 Geospatial Computing for Biological Systems 3
ABE 6433 Spectroscopic Sensing in Biological Systems 3
  Graduate Data Electives 0-3



Course Number Title Credit Hours
  A committee approved capstone project course, such as a DIS or CSE 8080 Directed Project. 3


Available Elective Courses

Course Number Title Credit Hours
CSE 6433 Artificial Intelligence 3
CSE 6833 Introduction to Algorithms 3
CSE 8443 Visualization 3
CSE 8673 Machine Learning 3
CSE 8833 Algorithms 3
CSE 9633 Topics in AI 3
ST 8263 Advanced Regression Analysis 3
ST 8353 Statistical Computing 3
ST 8413 Multivariate Statistical Methods 3
ST 8214 Design and Analysis of Experiments 3
ABE 6433 Geospatial Computing for Biological Systems 3
ABE 6443 Spectroscopic Sensing in Biological Systems 3
IE 6934 Information Systems for Industrial Engineering 3
IE 8743 Nonlinear Programming 3
IE 8793 Heuristics in Optimization 3
IE 6623 Engineering Statistics II 3
IE 8333 Production Control Systems II 3
IE 8353 Manufacturing Systems Modeling 3
MA 6183 Mathematical Foundations of Machine Learing 3



or ST


Special Topics 3

Admissions Requirements

Students seeking full admission into this program should apply as a classified student. Non-degree seeking students wishing to take classes offered through the Online program should apply as an Unclassified student.

Applications for the degree programs are reviewed two times a year. The application deadlines for those semesters are as follows:

  • Spring Enrollments need applications by November 1
  • Fall Enrollments need applications by June 1

An applicant for admission to graduate study must hold a bachelor's degree from a fully recognized four-year educational institution that has unconditional accreditation with appropriate regional accrediting agencies. They must meet the admission requirements of the Graduate School and the Data Science program.

Regular admission to graduate study in the program requires a minimum grade point average (last four semesters of undergraduate work) of 3.00/4.00. When a student is deficient in one of the criteria cited, the student's application, nevertheless, may be considered for admission based on the strength of other materials contained in the student's application.

The Graduate Record Examination (GRE) or Graduate Management Admission Test (GMAT) scores are NOT required for entry into this program.

Attention International Students

International students are required to take the Test of English as a Foreign Language (TOEFL) and score greater than 550. Detailed information regarding international applications can be found in the Graduate Catalog. Questions regarding international applications can be addressed to the Office of the Graduate School at

  • ETS is providing home testing for the TOEFL iBT test, and MSU is encouraging students to take advantage of this testing option. For those students applying who have taken the TOEFL within five years of the semester they plan to enroll and are unable to access the TOEFL iBT test from home, we will accept your previous test scores.


Admission Options

Domestic/International Classified Admissions

  1. Submit online application. You will choose Master of Science in Data Science as your Program of Study and Online Education as your campus.
  2. Statement of Purpose
  3. Three letters of recommendation
    • You will be asked to submit three names and three email addresses of individuals you are using as references. Once you click submit, these individuals will be sent an email from MSU, which will provide a link to an online form for completing their recommendations.
  4. One official transcript showing bachelor’s degree or progress toward degree. (For international students, please submit a copy in native language along with translated copies, if appropriate.)
  5. One official transcript showing ALL work after bachelor’s degree. (For international students, please submit a copy in native language along with translated copies, if appropriate.)
    • Electronic transcripts should be sent to: Mississippi State University, Graduate School. Only one copy of an electronic transcript is required.
    • Paper Transcripts Address (USPS):
      Mississippi State University
      The Office of the Graduate School
      P.O. Box G
      Mississippi State, MS 39762
    • Physical Street Address (for DHL, Fed Ex, UPS, DHS, etc.):
      Mississippi State University
      The Office of the Graduate School
      175 President Circle
      116 Allen Hall
      Mississippi State, MS 39762
  6. Payment of $60 non-refundable application processing fee for domestic students.
    Payment of $80 non-refundable application processing fee for international students.
  7. Once you are admitted, you will receive an email with complete instructions on registering for classes and contacting your advisor

Accessing Online Courses

Accessing Course Videos

Videos recorded during our on campus class sessions are uploaded for online students to view within our online course repository.  Online students will have access to course videos within 24 hours of the on campus course completion. Students should visit Engage to access the course videos. Instructions for viewing the recordings and downloading the recordings are offered below.

View and Download Videos

Instructions for viewing classes live or downloading videos, use our video download instructions.

If you experience technical difficulties or have any questions regarding the recording or format of our lecture capture, please contact:

IT Support & Staff
Bagley College of Engineering
Mississippi State University

Contact Information

Photo of Mindy Wolfe

Mindy Wolfe

Enrollment & Onboarding Coach

  • General Program Questions
  • Assistance with Admissions Process & Requirements
Photo of Anusha Rijal

Anusha Rijal

Retention & Engagement Coach

  • Current Student Inquires
  • Academic & Support Services Assistance
TJ Jankun Kelly Headshot

Dr. T.J Jankun-Kelly

Computer Science and Engineering

  • Graduate Co-coordinator
  • Associate Professor
Mohammad Sepehrifar Headshot

Dr. Mohammad Sepehrifar

Mathematics and Statistics

  • Graduate Co-coordinator
  • Associate Director and Professor