Data Science Minor
The Data Science Minor provides students with real-world skills in understanding and analyzing data. Students will learn basic programing skills, will develop necessary statistics skills, and will learn to apply these skills through substantive quantitative subject-matter focused coursework.
Minor Requirements
Minors require a minimum of
9 credits of upper-division (300-400 level) coursework.
Required Courses
Introductory Courses (6 credits)
| CS 138 | Programming For Data Science In Python I | 3.00 |
| DATA 101 | Introduction to Data Science | 3.00 |
Intermediate Level Courses (3 credits)
Complete one of the following courses:
| DATA 210 | Introduction to SQL for Data Science | 3.00 |
| DATA 220 | Research Methods for Data Science | 3.00 |
Advanced Quantitative Courses (6 credits)
Complete two courses from the following:
| DATA 310 | Data Visualization | 3.00 |
| DATA 320 | Introduction to Mathematical Modeling | 3.00 |
| DATA 330 | Statistical Methods for Data Science | 3.00 |
| DATA 410 | Exploratory Data Analysis | 3.00 |
| BIOL 416 | Bioinformatics | 3.00 |
| CHEM 421 | Physical Chemistry I | 3.00 |
| CHEM 445 | Organic Spectroscopy and Structure Determination | 4.00 |
| CRJ 302 | Quantitative Applications in Criminal Justice | 3.00 |
| ENV 480 | Geographic Information System for Environmental Management | 4.00 |
| FIN 301 | Principles of Managerial Finance | 3.00 |
| MATH 330 | Linear Algebra I | 3.00 |
| MATH 381 | Methods of Discrete Mathematics | 3.00 |
| MATH 352 | Probability and Statistics | 3.00 |
| or | |
| STAT 391 | Applied Statistics for Biological Sciences | 3.00 |
Students are encouraged to take
DATA 310,
DATA 320,
DATA 330, or
DATA 410 as one/both courses, but it is not required. Students may take
MATH 352 or
STAT 391, but only one can fulfill the requirement. Other courses may be approved on a case by case basis. Pre-requisite(s) vary; see the course description section on specific courses.
Data Science Capstone (3 credits)
Complete one of the following courses: