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.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 interdisciplinary Master of Science in Data Science degree program will provide students with broad training in managing, processing, and extracting value from large 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. The Agricultural Autonomy Concentration requires ABE 6463 Introduction to Imaging in Biological Systems, ABE 6900 Robotics for Biological Systems and CSE 6643 AI Robotics.

The interdisciplinary Master of Science in Data Science degree program will provide students with broad training in managing, processing, and extracting value from large 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. The Geospatial Science Concentration requires GR 6303 Principles of GIS, GR 6313 Advanced GIS and GR 6333 Remote Sensing of the Physical Environment.

The interdisciplinary Master of Science in Data Science degree program will provide students with broad training in managing, processing, and extracting value from large 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. The Manufacturing Analytics Concentration requires IE 6673 Reliability Engineering, IE 6683 Machine Learning with Industrial Engineering Applications and IE 8623 Advanced Data Analytics for Complex Systems.

The online Master of Applied Data Science (MADS) provides an opportunity for working professionals to gain a mastery of data science concepts along with practical, hands-on experience in using data science methods in their areas of expertise. Coursework provides deep engagement with data modeling, collection, analysis (including statistical, machine learning, and deep learning AI approaches), computation, and integration. To ensure the program is accessible to all learners who want to apply the methods and practices of Data Science to their professions, it was designed to require no prerequisites.

Learn how to integrate data science into classroom instruction in any field and prepare students to meet the growing demand for data science expertise in the context of the artificial intelligence revolution and the ongoing digital transformation of industry and society. The Graduate Certificate in Data Science Pedagogy is a program that requires a minimum of 12 credit hours and is designed to prepare K-14 instructors to integrate data science into instruction with the overall goal of preparing students to meet the growing demand for data science expertise in the context of ongoing digital transformation of industry: the process by which firms integrate digital technology into every aspect of operations and bring value to customers. To be credentialed to deliver data science instruction at the higher education level, students are required to take a minimum additional of 6 credit hours of course work to be selected by the students and approved by the Data Science Pedagogy Graduate Certificate committee. Organizations in every industry, including education that do not embrace digital transformation will struggle to survive the fourth industrial revolution with its dependence on automation through artificial intelligence and the blurring of boundaries between the physical and digital worlds. To remain competitive in this environment, Mississippi businesses require middle-skill and high-skill data science experts. Mississippi's education and workforce development system must meet this growing demand to remain economically competitive. Yet Mississippi's educators, like those in the rest of the nation, lack adequate preparation to infuse data science into their curricula and instruction. To meet this need, the certificate includes coursework with the twofold purpose of (1) helping instructors become literate in the field of data science by understanding the role data science experts play in improving the performance of institutions, organizations, business, and society; and (2) teaching instructors how to teach the practice of data science in their own classrooms, regardless of subject.