Data Science Minor Requirements
DATA SCIENCE MINOR
Students minoring in Data Science receive exposure to computational and applied statistical techniques. This minor provides a strong foundation for students preparing for employment in the data economy or graduate study. 6 courses are required to complete the minor.
MINOR REQUIREMENTS (6 Units)
- 1 introductory statistics course*:STAT 202-0 Introduction to Statistics, STAT 210-0 Introductory Statistics for the Social Sciences, STAT 232-0 Applied Statistics, or approved introductory statistics course from another department
(STAT 202 includes a brief introduction to the statistical programming language R, while STAT 210 instead spends more time covering the basic elements of mathematical probability)
- STAT 301-1 Data Science 1 with R or STAT 303-1 Data Science 1 with Python (pre-requisite introductory statistics) offered Fall quarter
- STAT 301-2 Data Science 2 with R (pre-requisite for STAT 301-2) or STAT 303-2 Data Science 2 with Python (pre-requisite STAT 303-1) offered Winter quarter
- STAT 301-3 Data Science 3 with R (pre-requisite STAT 301-2) or STAT 303-3 Data Science 3 with Python (pre-requisite STAT 303-2) offered Spring quarter
- STAT 302 Data Visualization
- 1 approved elective course relevant to the minor
*In the event that an introductory statistics course is a requirement for a student’s major/minor, an acceptable replacement course will be identified during advising. Replacement courses may be taken prior to, concurrent with, or after the required data science courses. Courses used to fulfill the requirements for a major/minor typically may not be used to fulfill the requirements for the Data Science Minor.
Students may receive credit for only one Data Science Sequence, STAT 301-1,2,3 Data Science with R or STAT 303-1,2,3 Data Science with Python.
If you are or are considering majoring/minoring in Statistics, please see the Data Science Minor for Statistics Majors page for modified requirement information
Expectations and coursework
Students will develop data acumen by learning how to ethically and effectively collect, process, explore, communicate, and make decisions with data and how to combine these components into an efficient data workflow.
The core courses (Data Science 1, 2, 3, and Data Visualization) are designed for students to develop the knowledge and skills needed to build an appropriate data workflow through project work. In each of these courses students will be expected to complete 1-2 weekly assignments and a final data project focused on a dataset they have sourced. Students should be prepared to dedicate approximately 7-12 hours per week outside of class to course work.
Declaring the Data Science Minor
Space in the core courses for the minor in Data Science (STAT 301-1,2,3/STAT 303-1,2,3 and STAT 302), is limited and students who declare are assigned to a Data Science Minor Cohort. Students who are interested in pursuing the minor should add themselves to the Data Science Minor Declaration Interest List as early as possible.
The Data Science Minor Cohorts reflect the academic year the students in the cohort are assigned to take the core Data Science courses. For example, students in the 2021-22 Data Science Minor Cohort would take their 4 core STAT data science minor courses in academic year 2021-2022. Students are only guaranteed seats in the 4 core data science courses in their assigned Cohort year.
Additionally, cohorts are broken into two tracks, the R track and the Python track. Students wishing to declare indicate if they have a track preference.
The assignment of students to a Data Science Minor Cohort and declaration of the minor happens annually in spring quarter. Assignment to a cohort is based on availability, track preference, and other factors. We begin filling cohorts up to three years in advance.
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