Data Science Minor
Students minoring in data science receive exposure to computational and applied statistical techniques. This minor provides a strong foundation for graduate work and academic preparation in the area.
| Course | Title |
|---|---|
| Minor Requirements (6 units) | |
| 1 introductory course: | |
| STAT 202-0 | Introduction to Statistics |
| or STAT 210-0 | Introductory Statistics for the Social Sciences |
| or STAT 232-0 | Applied Statistics |
or approved introductory statistics course from another department | |
| 3-course data science sequence seleted from: 1 | |
| STAT 301-1 & STAT 301-2 & STAT 301-3 | Data Science 1 with R and Data Science 2 with R and Data Science 3 with R |
| or STAT 303-1 & STAT 303-2 & STAT 303-3 | Data Science 1 with Python and Data Science 2 with Python and Data Science 3 with Python |
| 1 required data visualization course: | |
| STAT 302-0 | Data Visualization |
| 1 approved elective course relevant to the minor | |
| 1 | Students may receive credit for only one Data Science sequence, STAT 301-1,2,3 with R or STAT 303-1,2,3 with Python. |
Courses used to fulfill the requirements for the minor in data science may not be used to fulfill the requirements for another major/minor except where permitted by Weinberg College double-counting rules. When necessary (for example when a student plans to complete a major in statistics and a minor in data science), students can consult an adviser in the Department of Statistics about selection of replacement course(s) to satisfy the credit requirements of the data science minor.