Data Science
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.
| Course Number | Description | Prequisites | Credits |
|---|---|---|---|
| DS 110 | Introduction to Data Science | 3 credits | |
| MA 220 | Intro to Prob and Stats or any other Intro Stats from other depts. | MA 130 | 4 credits |
| CS 110 | Computer Sci. I | 3 credits | |
| MA 116 | Discrete Structures | High School Algebra | 4 credits |
| MA 130 | Calculus I | 4 credits | |
| MA 160 | Linear Alg. | MA 130 | 3 credit |
| CS 370 | Database Mgmt Sys | CS 110 | 3 credits |
| DS 352 | Machine Learning | DS 110, CS 110 | 3 credits |
| IM 242 | Information Visualization | DS 110 or IM 110 | 3 credits |
| MA 321 | Multivariate Stats | A stat class and MA 130 | 3 credits |
| DS 325 | DS Consulting | A stat class and CS 110 | 3 credits |
| DS 375 | Big Data | CS 370 and DS 110 | 3 credits |
| DS 210 | Data Acquisition | DS 110 and CS 110 | 3 credits |
cognate area courses 12 credits
Total credits = 54
Upper-level Credit Hours (>=300): 18
One CW Course within the POE: DS 325