Data Science Secondary Emphasis
The overarching goal of data science is to be able to process, organize, and analyze large data sets to distill meaningful patterns and trends. Data science students will learn how to use the tools and problem-solving skills of mathematics, computer science and application domains to gather information from complex, multidimensional data sets. The secondary emphasis ensures exposure to the tools of statistics, data and database management, visualization, machine learning, and application of data science to a variety of fields.
| Course Number | Description | Prequisites | Credits |
|---|---|---|---|
| DS 110 | Introduction to Data Science | 3 credits | |
| MA 220 or BI 305 or PY 214 or EB 211 or ESS 230 |
Intro to Prob and Stats or any other Intro Stats from other depts. | 3-4 credits | |
| MA 321 or PY 406 |
Multivariate Statistical Methods or Advanced Stats for Psychology |
MA 130 or MA 160 |
3-4 credits |
| CS 370 | Database Management Systems | CS 110 | 3 credits |
| IM 242 | Information Visualization | 3 credits | |
| CS 352 | Machine Learning | 3 credit | |
| MA 325 or BI 380 |
Statistical Consulting or Bio Research (or an approved capstone course applying data science) |
3-4 credits |
Total credits = 21-24