MS Mathematics: Data Science
Students in the University of Minnesota Master of Science: Mathematics with an emphasis in Data Science program dive deep into areas such as linear algebra, probability theory, calculus, optimization, and machine learning algorithms. These are the fundamental pillars on which modern data science stands. At its core, data science relies on a solid foundation of mathematics – the universal language that enables us to model complex phenomena, extract meaningful patterns, and make informed predictions.
Plan type and coursework
The Master of Mathematics with an emphasis in Data Science is completed as a Plan C Master's degree that requires 10 courses. The minimum GPA of the Master’s program is 3.0. Coursework used to fulfill the degree requirements must be taken on a grade basis when offered. Students entering the Master’s program are required to have completed an undergraduate degree prior to matriculation into the program.
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Data Analysis Requirement – 2 Courses
Data Analysis Requirement – 2 Courses
- MATH 5465: Mathematics of Data Analysis I
- MATH 5466: Mathematics of Data Analysis II
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Probability Requirement – 1 Course
Probability Requirement – 1 Course
Pick one:
- MATH 5651: Probability and Statistics Theory
- MATH 8651: Probability Theory I
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Numerical Methods Requirement – 1 Course
Numerical Methods Requirement – 1 Course
Pick one:
- MATH 5485: Numerical Methods
- MATH 8441: Numerical Analysis and Scientific Computing I
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Data Science Electives – 4 Courses
Data Science Electives – 4 Courses
- MATH 5652: Stochastic Processes
- MATH 8652: Probability Theory II
- MATH 8442: Numerical Analysis and Scientific Computing II
- MATH 5486: Numerical Methods
- MATH 5490: Topics in Applied Mathematics
- MATH 8600: Topics in Applied Mathematics
- MATH 5707: Graph Theory
- MATH 5711: Linear Programming
- MATH 5535: Dynamical Systems
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Outside Coursework – 2 Courses
Outside Coursework – 2 Courses
- CSCI 5521 ML Fundamentals
- CSCI 5525 Advanced ML
- CSCI 5527 Deep Learning
- CSCI 5541 Natural Language Processing
- CSCI 5980 Topics
- CSCI 8980 Topics
- IE 8564 Optimization for ML
- IE 5571/8571 Reinforcement Learning
- IE 5133 Operations Research for Data Science
- STAT 5302 Applied Regression Analysis
- STAT 5421 Categorical Data
- STAT 5701 Statistical Computing
- STAT 5511 Time Series Analysis
Other courses in or outside of Mathematics may be used with advisor and DGS approval. The completion of a formal minor in Data Science, Computer Science, or Statistics will meet the outside coursework requirement of this degree. Core or Elective courses in Mathematics as listed above may be used to fulfill the outside coursework requirement.
Tuition and funding
Offers of admission to our MS Mathematics: Data Science program do not come with an offer of funding. Students can find a number of financial aid opportunities through the Funding page of the Graduate School’s website.