Data Science majors must earn a minimum of 60 credits subject to the restrictions outlined below.
Core Requirements:
Course | Title | Credits |
---|---|---|
MATH 1830 | Elementary Statistics | 3 |
MATH 2130 | Discrete Structures | 3 |
or MATH 2730 | Discrete Mathematics | |
MATH 2640 | Calculus and Analytic Geometry I | 4 |
MATH 2740 | Calculus and Analytic Geometry II | 4 |
MATH 3230 | Linear Algebra | 3 |
MATH 4030 | Statistical Methods with Applications | 3 |
MATH 4050 | Applied Regression Analysis | 3 |
STAT 2030 | Data Visualization and Analysis | 3 |
COMPUTER 1430 | Introduction to Computer Programming | 3 |
COMPUTER 2430 | Object-Oriented Programming | 3 |
COMPUTER 3630 | Database Design and Implementation | 3 |
ENVSS 3230 | Geographic Information Systems | 4 |
DATASCI 2010 | Data Science I | 3 |
DATASCI 2510 | Data Science II - Intermediate Data Science | 3 |
DATASCI 3010 | Data Science Ethics | 3 |
DATASCI 4900 | Data Science Capstone | 3 |
Focus Area Requirement (a minimum of 9 credits in one of the following areas):
Biology - Molecular/Genetics
Course | Title | Credits |
---|---|---|
BIOLOGY 3330 | Genetics | 3 |
BIOLOGY 3470 | Systematics and Evolutionary Analysis | 3 |
ENVSS 3340 | Biogeography | 3 |
Biology - Ecological
Course | Title | Credits |
---|---|---|
BIOLOGY 3450 | Ecology and Evolution | 3 |
BIOLOGY 3460 | Ecological Methods and Research | 3 |
ENVSS 3340 | Biogeography | 3 |
Mathematics/Statistics
Course | Title | Credits |
---|---|---|
STAT 3230 | Experimental Design and Analysis | 3 |
STAT 4130 | Applied Categorical Data Analysis | 3 |
STAT 4230 | Applied Nonparametric Statistics | 3 |
MATH 3730 | Numerical Analysis | 3 |
Business (a minor in Business is recommended for this focus area)
Course | Title | Credits |
---|---|---|
BUSADMIN 3640 | Financial Markets and Institutions | 3 |
BUSADMIN 3700 | Marketing Research | 3 |
BUSADMIN 3930 | Investments | 3 |
BUSADMIN 4030 | Financial Decision Making | 3 |
BUSADMIN 4120 | Operations Management | 3 |
BUSADMIN 4170 | Predictive Analytics | 3 |
Spatial
Course | Title | Credits |
---|---|---|
ENVSS 3520 | Remote Sensing of the Environment | 3 |
ENVSS 4040 | Python for GIS | 3 |
ENVSS 4330 | Advanced Geographic Information Systems | 4 |
Computer Science
Course | Title | Credits |
---|---|---|
COMPUTER 2630 | Data Structures | 3 |
COMPUTER 3030 | Artificial Intelligence | 3 |
COMPUTER 4030 | Machine Learning | 3 |
Additional Requirement: Cumulative GPA of 2.5 minimum.
Recommended: Internship or Undergraduate Research Experience