Data Science Minor Requirements
DATA SCIENCE MINOR
Students minoring in Data Science receive exposure to computational and machine learning techniques. This minor provides a strong foundation for students preparing for employment in the data economy or graduate study. 7 courses are required to complete the minor.
MINOR REQUIREMENTS (7 Units)
- 1 introductory programming course: STAT 201-0 Introduction to Programming for Data Science or COMP_SCI 110-0. Students who take COMP_SCI 110-0 are responsible for independently learning topics covered in STAT 201-0 that are not covered in COMP_SCI 110-0 before taking a STAT course for which STAT 201-0 is a prerequisite. STAT 201-0 topics not covered in COMP_SCI 110-0
- 1 introductory statistics course*:STAT 202-0 Introduction to Statistics and Data Science or STAT 210-0 Introduction to Probability and Statistics or STAT 232-0 Applied Statistics, or approved introductory statistics course from another department
(STAT 202 includes a basic 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 STAT 201-0 and an introductory statistics course) offered Fall quarter
- STAT 301-2 Data Science 2 with R (pre-requisite STAT 301-1) 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 (pre-requisite STAT 201-0 and an introductory statistics course)
- 1 approved elective course relevant to the minor – see Data Science Minor Approved Electives for more information
*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 another major/minor typically may not be used to fulfill the requirements for the Data Science Minor. See Weinberg rules for double counting.
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 a Statistics major or are considering majoring/minoring in Statistics, please see the Data Science Minor for Statistics Majors page for modified requirement information.
If you are a MMSS student, please see the Undergraduate Catalog or the MMSS website for requirements specific to MMSS students doing the Minor in Data Science.
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 Minor in Data Science
There is a declaration period for the minor held annually each year in Spring quarter. However, the steps for declaring start with completing The Data Science Interest List as soon as possible after it opens on September 1.
Students who wish to declare the minor must follow the declaration process steps listed on the Declaring the Minor in Data Science page
Questions
Please contact stats@northwestern.edu