Data Science in Business (Certificate)
To see more about what you will learn in this program, visit the Learning Outcomes website!
Plan Requirements
| Code | Title | Hours | Counts towards |
|---|---|---|---|
| Required DSC Courses: At least one course from each category | 6 | ||
| Data Communication | |||
| Introduction to Data Visualization | |||
| Data Communication | |||
| Ethics, Policy, & Privacy | |||
| Data Science for Social Good | |||
| Data Management & Analysis | |||
| Introduction to R/Python for Data Science (DSC 201 will not count for students who take ST 308 as a coreq for BUS 351.) | |||
| Machine Learning and AI | |||
| Exploring Machine Learning | |||
| Electives or Internships & Capstones | |||
| Data Wrangling and Web Scraping | |||
| See the published special topics list for courses accepted within a category | |||
| Introductory Special Topics in Data Science | |||
or DSC 495 | Special Topics in Data Science | ||
or DSC 595 | Graduate Special Topics in Data Science | ||
| Required Depth Courses: Two courses from the following | 6 | ||
| 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) | |||
| Analytics: From Data to Decisions (Prerequisite: BUS 351) | |||
| NOTE 1: DSC 295, DSC 495, and DSC 595 courses must be individually approved for the certificate. | |||
| NOTE 2: Students pursuing multiple Data Science Academy credentials must have at least 2 distinct 1-credit DSC courses and 2 distinct 3-credit depth courses between any two credentials (8 distinct credits total). | |||
| NOTE 3: Per university requirements courses already used to satisfy two or more credit requirements cannot also be used to satisfy the data science certificate (or any third requirement). | |||
| Total Hours | 12 | ||