Undergraduate courses

The data science bachelor's degree at the University of Minnesota offers a comprehensive curriculum in math, science, computer science, statistics, industrial engineering, and technical writing, plus technical electives and a capstone project. In addition, all students will also take courses to meet the University's liberal education requirement.

Sample graduation plans

The sample graduation plan for the data science major includes all required courses in the order they need to be taken. While graduation is not guaranteed in four years, the plans show how to stay on track toward reaching that goal.

Note: Data science majors cannot pursue a computer science minor.

Required mathematics coursework

  • MATH 1371 or 1271 or 1571H - Calculus I (4 cr)
  • MATH 1372 or 1272 or 1572H - Calculus II (4 cr)
  • MATH 2374 or 22263 or 2573H - Multivariable Calculus (4 cr)
  • CSCI 2033 - Elementary Computational Linear Algebra (4 cr) or acceptable substitution

Required science coursework

  • PHYS 1301W/1401V - Introductory Physics for Science and Engineering I (4 cr)
  • Second science course - Choose from PHYS 1302W, CHEM 1061&1065, CHEM 1062&1066, ESCI 2201, PSY 3011, or GCD 3022 (3 or 4 cr)

Required computer science coursework

  • CSCI 1133 - Introduction to Computing and Programming Concepts (4 cr) *or CSCI 1103, 1113, or CSCI 1901 for CSCI/DSCI double majors who have CSCI 1913 or CSCI 1902 instead of CSCI 2081; EE 1301 is not accepted in place of CSCI 1133
  • CSCI 2081 - Introduction to Software Development and Data Structures (4 cr) (offered starting Fall 2020) *or CSCI 1933 AND CSCI 3081W for CSCI/DSCI double majors
  • CSCI 3041 - Introduction to Discrete Structures and Algorithms (4 cr) (offered starting Spring 2021) *or CSCI 2011 AND CSCI 4041 for CSCI/DSCI double majors
  • CSCI 3061 - Introduction to Systems and Systems Programming (4cr) (offered starting Spring 2021) *or CSCI 2021 AND CSCI CSCI 4061 for CSCI/DSCI double majors
  • CSCI 4707 - Practice of Database Systems (3 cr)
  • CSCI 5521 - Introduction to Machine Learning (3 cr) or CSCI 5523 - Introduction to Data Mining (3 cr) or STAT 4052 - Introduction to Statistical Learning (4 cr)

Required statistics coursework

  • STAT 3021 - Introduction to Probability and Statistics (3 cr) or STAT 3011 - Intro to Statistical Analysis AND STAT 3032 - Regression and Correlated Data
  • STAT 3301 - Regression and Statistical Computing (4 cr) (offered starting Fall 2021; students can take STAT 3701 as a substitution for this requirement in Fall 20 and Spring 21)
  • STAT 4051 - Applied Statistics I (4 cr)
  • STAT 5101 - Theory of Statistics I (4 cr) or MATH 5651 - Basic Theory of Probability and Statistics (4 cr)
  • STAT 5102 - Theory of Statistics II (4 cr)

Required industrial engineering coursework

  • IE 3013 - Optimization for Machine Learning (4 cr) (offered starting Fall 2021)
  • IE 5533 - Operations Research for Data Science (3 cr) (offered starting Fall 2022; students can take IE 3011 or IE 5531 (Optimization) AND IE 4011 or IE 5532 (Stochastic Modeling) as a substitution for this requirement until Fall 2022; students will be able to use both courses in the curriculum (sub for IE 5533 + technical elective))

Required technical writing

  • WRIT 3562W -Technical and Professional Writing (4 cr)

Capstone

  • DSCI 4093 - Senior Project (offered starting TBD; students can use CSCI 5994 Directed Research as a substitution)

Required upper division technical elective

(18 credits minimum)

  • STAT 5201 - Sampling Methodology in Finite Populations (3 cr)
  • STAT 5401 - Applied Multivariate Methods (3 cr)
  • STAT 5421 - Analysis of Categorical Data (3 cr)
  • STAT 5511 - Time Series Analysis (3 cr)
  • STAT 5601 - Nonparametric Methods (3 cr)
  • STAT 4893W - Communication for Statisticians (3 cr)
  • STAT 5931 - Topics in Statistics (3 cr)
  • IE 3011 - Optimization I (4 cr)
  • IE 3012 - Optimization II (4 cr)
  • IE 5111 - Systems Engineering I (2 cr)
  • IE 5113 - Systems Engineering II (4 cr)
  • IE 5531 - Engineering Optimization I (4 cr)
  • IE 5553 - Simulation (4 cr)
  • IE 5541 - Project Management (4 cr)
  • IE 5545 - Decision Analysis (4 cr)
  • IE 5561 - Analytics and Data-Driven Decision Making (4 cr)
  • IE 5545 - Decision Analysis (4 cr)
  • EE 4541 - Digital Signal Processing (3 cr)
  • EE 5239 - Introduction to Nonlinear Optimization (3 cr)
  • EE 5251 - Optimal Filtering and Estimation (3 cr)
  • EE 5351 - Applied Parallel Programming (3 cr)
  • EE 5355 - Algorithmic Techniques for Scalable Many-Core Computing (3 cr)
  • MATH 4242 - Applied Linear Algebra (4 cr)
  • MATH 4428 - Mathematical Modeling (4 cr)
  • MATH 5467 - Introduction to the Mathematics of Image and Data Analysis (4 cr)
  • MATH 5652 - Introduction to Stochastic Processes (4 cr)
  • CSCI 4131 - Internet Programming (3 cr)
  • CSCI 4511W - Introduction to Artificial Intelligence (4 cr) or CSCI 5511 - Artificial Intelligence I (3 cr)
  • CSCI 5105 - Introduction to Distributed Systems (3 cr)
  • CSCI 5115 - User Interface Design, Implementation and Evaluation (3 cr)
  • CSCI 5117 - Developing the Interactive Web (3 cr)
  • CSCI 5123 - Recommender Systems (3cr)
  • CSCI 5125 - Collaborative and Social Computing (3 cr)
  • CSCI 5271 - Introduction to Computer Security (3 cr)
  • CSCI 5302 - Analysis of Numerical Algorithms (3 cr)
  • CSCI 5304 - Computational Aspects of Matrix Theory (3 cr)
  • CSCI 5451 - Introduction to Parallel Computing (3 cr)
  • CSCI 5461 - Functional Genomics, Systems Biology, and Bioinformatics (3 cr)
  • CSCI 5481 - Computational Techniques for Genomics (3 cr)
  • CSCI 5512 - Artificial Intelligence II (3 cr)
  • CSCI 5525 - Machine Learning (3 cr)
  • CSCI 5561 - Computer Vision (3 cr)
  • CSCI 5609 - Visualization (3 cr)
  • CSCI 5708 - Architecture and Implementation of Database Management Systems (3 cr)
  • CSCI 5715 - From GPS and Virtual Globes to Spatial Computing (3 cr)
  • CSCI 5751 - Big Data Engineering and Architecture (3 cr)
  • CSCI 5801 - Software Engineering I (3 cr)
  • CSCI 5802 - Software Engineering II (3 cr)