The Data Science Minor is an interdisciplinary specialization that enables students to gain the skills necessary to perform data science tasks in conjunction with the skills that they learn in their major. In this Minor, students gain an understanding of key data science concepts such as how to program using data, use statistics on data, and how to use machine learning and statistical models. The Minor in Data Science is an interdisciplinary and interdepartmental undergraduate specialization administered through the Faculty of Science.
Admission to the Minor in Data Science: Students must apply to enter the Minor in Data Science through a process administered jointly by the Departments of Computer Science and Statistics. Applications are accepted once per year, in spring. Applicants must have their home faculty approval to join the minor. See Faculty of Science Minor Options. The application can be accessed at the Data Science Minor website.
Minor in Data Science
This minor consists of 33 credits, of which 18 must be at the 300-level or above.
Lower-Level Requirements
- Data Science: 3 credits of DSCI_V 100.
- Statistical Inference: 3 credits of STAT_V 201.
- Pre-requisites for required upper-level courses
- Programming: 6 credits given by the prerequisites for CPSC_V 330. For most non-CS majors, we recommend CPSC_V 103 followed by CPSC_V 203.
- Math: 3 credits given by the prerequisites for STAT_V 301.
Upper-Level Requirements
18 credits selected as follows:
- STAT_V 301
- CPSC_V 330
- One of DSCI_V 430, CPSC_V 430
- Three of the following five options:
- DSCI_V 310
- DSCI_V 320
- CPSC_V 416
- One of CPSC_V 368, CPSC_V 304, COMM_V 437
- One of COMM_V 335, COMM_V 365, COMM_V 414, COMM_V 415, CPSC_V 322, CPSC_V 340, CPSC_V 406, CPSC_V 447, ECON_V 398, ECON_V 425, EOSC_V 440, EOSC_V 410, INFO_V 419, LING_V 342, MATH_V 441, MATH_V 442, MICB_V 405, MICB_V 425, NSCI_V 303, PHYS_V 410, PSYC_V 359, STAT_V 406, STAT_V 447B, STAT_V 450