Program Co-Directors: Daniel Rowe, Ph.D and Michael Zimmer, Ph.D
Data Science is the emerging field that seeks to extract and quantify knowledge from data. The interdisciplinary Data Science minor (INDS) integrates statistics and mathematics with computer science, allowing students to develop the knowledge and skills necessary to discover and quantify new knowledge from data. Those prepared to integrate advanced technology with modern statistical and mathematical practices have the opportunity to use data in action to benefit society. Data scientists turn data into knowledge.
Interdisciplinary Minor in Data Science
The interdisciplinary data science minor consists of 19 credit hours of courses, including five required computer science and mathematics courses (16 credit hours) and an additional 3 credit hours of an advanced elective.
Course List | Code | Title | Hours |
| |
| COSC 1010 | Introduction to Software Development | 4 |
| COSC 4610 | Data Mining | 3 |
| 6 |
| Modern Elementary Statistics
and Introduction to Regression and Classification | |
| Statistical Methods
and Regression Analysis | |
| |
| COSC 3570 | Introduction to Data Science | 3 |
| or MATH 3570 | Introduction to Data Science |
| 3 |
| Bioinformatics Algorithms | |
| Professional Ethics in Computer & Data Science | |
| Visual Analytics | |
| Fundamentals of Artificial Intelligence | |
| Principles of Database Systems | |
| Linear Algebra and Matrix Theory | |
| Theory of Probability | |
| Mathematical Statistics | |
| Computational Statistics | |
| Time Series Analysis | |
| Regression Analysis | |
| Bayesian Statistics | |
| Total Credit Hours: | 19 |
Notes:
- Other courses may be approved as an advanced elective with the consent of the departments.
- The MATH 1700 Modern Elementary Statistics and MATH 2780 Introduction to Regression and Classification sequence is recommended for students without a background in calculus. With the departments consent, MATH 1700 Modern Elementary Statistics may substituted with an equivalent statistics course.
- The MATH 4720 Statistical Methods and MATH 4780 Regression Analysis sequence is recommended for students who have successfully completed a college level calculus course and are comfortable with calculus. MATH 4740 Biostatistical Methods and Models may be substituted for MATH 4720 Statistical Methods.
