Data Science
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 already have a primary specialization, and applications will not be accepted once the student has gained 4th year standing. 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 100.
- Statistical Inference: 3 credits of STAT 201.
- Pre-requisites for required upper-level courses
- Programming: 6 credits given by the prerequisites for CPSC 330. For most non-CS majors, we recommend CPSC 103 followed by CPSC 203.
- Math: 3 credits given by the prerequisites for STAT 301.
Upper-Level Requirements
18 credits from the following:
STAT 301, CPSC 330, and four of the following six options:
- DSCI 310
- DSCI 320
- CPSC 416
- One of CPSC 368, CPSC 304, COMM 437
- CPSC 430
- One in-discipline data science course selected from COMM 335, COMM 365, COMM 414, COMM 415, CPSC 322, CPSC 340, CPSC 406, ECON 323, ECON 398, ECON 425, EOSC 410, INFO 419, LING 342, MATH 441, MATH 442, MICB 405, MICB 425, PHYS 410, PSYC 359, STAT 406, STAT 447B, STAT 450.
