Data Science Requirements
- Familiarize students with the techniques and foundational material necessary for students to pursue future studies or careers in data science.
- Ensure that students understand the ethical implications inherent in the data science field.
- Develop the knowledge, skills, and experiences necessary to properly deal with data (data acumen).
- Ensure that students can properly communicate data science ideas and results to both broad and specialized audiences.
- Students will gain the ability to apply knowledge of data science to other disciplines
- Students will develop their data acumen.
- Students will be able to demonstrate an understanding of the ethical implications inherent in the data science discipline.
- Students will be able to communicate data science ideas and results to both broad and specialized audiences effectively using presentation skills and visualizations.
This program is available via classroom (the majority of instruction is face-to-face). Courses may not be taken S-N unless offered S-N only.
A minimum GPA of 2.00 is required in the minor to graduate. The GPA includes all, and only, University of Minnesota coursework.
Grades of "F" are included in GPA calculation until they are replaced.
- STAT 1601 - Introduction to Statistics [M/SR] (4.0 cr) or STAT 2601 - Statistical Methods [M/SR] (4.0 cr)
- CSCI 1201 - Introduction to Digital Media Computation [M/SR] (4.0 cr) or CSCI 1251 - Computational Data Management and Manipulation [M/SR] (4.0 cr) or CSCI 1301 - Problem Solving and Algorithm Development [M/SR] (4.0 cr)
- IS 1091 - Ethical and Social Implications of Technology [E/CR] (2.0 cr)
Introduction to Data Science
- CSCI 2701 - Introduction to Data Science [M/SR] (4.0 cr) or STAT 2701 - Introduction to Data Science [M/SR] (4.0 cr)
Intermediate Data Science
- CSCI 3701 - Intermediate Data Science (4.0 cr) or STAT 3701 - Intermediate Data Science (4.0 cr)
At least one course from the list below or discipline approved course. Take 1 or more course(s) from the following:
- STAT 3501 - Survey Sampling [M/SR] (4.0 cr)
- STAT 4601 - Biostatistics (4.0 cr)
- STAT 4631 - Design and Analysis of Experiments (4.0 cr)
- STAT 4651 - Applied Nonparametric Statistics (4.0 cr)
- STAT 4671 - Statistical Computing (4.0 cr) •STAT 4681 - Introduction to Time Series Analysis (4.0 cr)
Students are required to complete one of the following sub-plans.
Computer Science: Data Structure, Algorithms and Complexity
- CSCI 2101 - Data Structures [M/SR] (5.0 cr)
- CSCI 3501 - Algorithms and Computability (5.0 cr)
Statistics: Multivariate Statistics
- STAT 3611 - Multivariate Statistical Analysis [M/SR] (4.0 cr)