Minor in Data Science
The Data Science minor equips students with the skills to collect, analyze and interpret complex data in a variety of contexts. Through a blend of statistical methods, computational tools and ethical considerations, students learn to transform data into meaningful insights and informed decisions.
Some majors may not be eligible to pair with this minor. See the Minor Restrictions list for details.
Prescott Minor Requirements
| DSCI 150 | Data Science I: Introduction | 3 |
| DSCI 151 | Data Science II: Foundations | 3 |
| Choose Three of the Following: | 9 | |
| Big Data Analytics and Machine Learning | ||
| Ethics of Data Science | ||
| Data Acquisition and Manipulation | ||
| Data Visualization | ||
| Statistics for Data Science and Statistical Software * | ||
| Cloud Computing | ||
| Introduction to Discrete Structures | ||
| Introduction to Linear and Abstract Algebra and Machine Learning * | ||
| Total Credits | 15 | |
At least six (6) credit hours upper-level (300+ level), and at least six (6) of which are distinct from otherwise
major requirements.
- *
Both courses must be completed for a total of six hours towards the nine-hour requirement.