Program Overview
The Minor in Data Science provides a rigorous study of the data analysis lifecycle with a foundation of computer programming and statistics. This minor is designed for students who want to supplement their major domain with the knowledge and skills needed to manage and analyze large data sets.
Learning Outcomes
- Students completing the program will have the ability to apply theory, techniques, and tools throughout the data analysis lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.
- Students completing the program will have the ability to apply principles of computing and statistics to identify solutions for data intensive applications.
Undergraduate Policies
For undergraduate policies and procedures, please review the Undergraduate Academics section of the General Bulletin.
Program Requirements
The Minor in Data Science consists of six courses and 18 credit hours:
Course List Code | Title | Credit Hours |
CSDS 132 | Programming in Java | 3 |
CSDS 133 | Introduction to Data Science | 3 |
CSDS 234 | Structured and Unstructured Data | 3 |
STAT 301 | Introduction to Probability for Statistics | 3 |
or STAT 312 | Basic Statistics for Engineering and Science |
or STAT 312R | Basic Statistics for Engineering and Science Using R Programming |
or MATH 380 | Introduction to Probability |
CSDS 312 | Introduction to Data Science Systems | 3 |
or CSDS 313 | Introduction to Data Analysis |
| Introduction to Data Structures | |
| Discrete Mathematics | |
| Introduction to Data Science Systems | |
| Introduction to Data Analysis | |
| Data Mining for Big Data | |
| Introduction to Machine Learning | |
| Introduction to Database Systems | |
| Introduction to Linear Algebra for Applications | |
| Linear Algebra | |
| Data Analysis and Linear Regression Models | |
| Multivariate Analysis and Data Mining | |
| Mathematical Statistics | |
Total Credit Hours | 18 |
Students interested in pursuing graduate work in data science are encouraged to take CSDS 233 and MATH 201 or MATH 307.