Data Science in Business (Minor)
The Undergraduate Minor of Data Science in Business is a 15 credit interdisciplinary credential that offers a path towards developing essential skills in data science with depth in Business (BUS) content. Students who pursue this minor will have the opportunity to learn from data science instructors & practitioners, and Business faculty in industry & academia, alongside their peers from various colleges. Students will pursue courses in data management, communication, applications, ethics, business, and more, in addition to choosing from electives of interest.
Contact
Data Science and AI Academy
Plan Requirements
Required Courses
| Code | Title | Hours |
|---|---|---|
| Required DSA Courses: At least one course from each category | 6 | |
| Categories and Corresponding Category Numbers (in parentheses) | ||
Data Management & Analysis (1) | ||
Data Communication (2) | ||
Ethics, Policy, & Privacy (3) | ||
Machine Learning and AI (4) | ||
Electives or Internships & Capstones (5) | ||
| Course Options and Corresponding Category Notes | ||
| Introduction to R/Python for Data Science (Introduction to R/Python for Data Science (DSA 201 will not count for students who take ST 308 as a coreq for BUS 351)) (1) | ||
| Introduction to Data Visualization (2) | ||
| Data Communication (2) | ||
| Introduction to AI Ethics (3) | ||
| Data Science for Social Good (3) | ||
| Introduction to Data Science for Cybersecurity (3) | ||
| Measuring Success (1) | ||
| Data Wrangling and Web Scraping (5) | ||
| Exploring Machine Learning (4) | ||
| Introductory Special Topics in Data Science See semesterly list of special topics courses accepted within a category | ||
| Special Topics in Data Science See semesterly list of special topics courses accepted within a category | ||
| Graduate Special Topics in Data Science See semesterly list of special topics courses accepted within a category | ||
| Courses not used for a category requirement may be applied to fulfill "Electives or Internships & Capstones (5)" | ||
| Required Depth Courses | 9 | |
| Introduction to Business Analytics (Prerequisites: BUS 340 and [BUS 350, or ST 312, or ST 370, or ST 372]; Corequisite: ST 307 or ST 308) | ||
| Choose 2 of the following: | ||
| Database Management (Prerequisites: BUS 340 or ACC 340) | ||
| Analytics: From Data to Decisions (Prerequisite: BUS 351) | ||
| Business Analytics Practicum (Prerequisites: BUS 351 and BUS 458) | ||
| NOTE: Students pursuing multiple Data Science and AI Academy credentials must have at least 2 distinct 1-credit DSA courses and 2 distinct 3-credit depth courses between any two credentials (8 distinct credits total). | ||
| Total Hours | 15 | |