Data Science, Minor
Program Description
The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, deeper knowledge of probability and statistics, and learn tools to analyze big data sets and to design of the experiments.
Admissions Requirements
To be enrolled in the university as a math or science major. To be enrolled in the university. Calculus I, Calculus II, and some programming skills required. Calculus III preferred.
Program Requirements
| Code | Title | Hours |
|---|---|---|
| CORE COURSES: | ||
| MATH 3342 | Applied Probability and Statistics | 3 |
| or MATH 3345 | Statistical Modeling and Data Analysis | |
| MATH 3347 | Introduction to Probability | 3 |
| MATH 3349 | Principles of Data Science | 3 |
| MATH 3311 | Linear Algebra | 3 |
| Electives | ||
| Select three of the following: | 9 | |
| Geospatial Mathematical Techniques | ||
or GISC 3300 | Geospatial Mathematical Techniques | |
| Linear Optimization and Decisions | ||
| Introduction to Machine Learning | ||
| Applied Regression Analysis | ||
| Introduction to Mathematical Statistics | ||
| Applied Modeling | ||
| Total Hours | 21 | |