Data Science
Data Science course descriptions
Faculty
Wendy Weber (chair), Erik Insko, Stephen Fyfe, Russ Goodman, Mark Mills, Alexey Pronin, Michael Thompson.
Statement of Philosophy
Data is everywhere in today’s society. A minor in data science is a valuable way for students to learn a variety of concepts, tools, and modern technologies connected to data analysis. Further, students minoring in data science will have enhanced abilities to visualize, interpret, and communicate the results of analyses involving data. These are all essential skills for students to apply in the context of a variety of disciples, including their chosen field of study.
Minor Restriction
Students declaring a computer science major or mathematics major may not also declare a data science minor. Students declaring an economics major or an actuarial science major must take an elective outside of their major.
Data Science Minor Requirements (23-24 credits)
- Complete all of the following:
COSC 110 Introduction to Computer Science (3)
MATH 131 Calculus I (4)
MATH 215 Applied Statistics (4) or approved disciplinary statistics course
DATA 210 Introduction to Data Science (3)
DATA 310 Data Visualization (3)
DATA 440 Applied Machine Learning (3)
- Complete one of the following:
COSC 130 Data Structures (3)
COSC 210 Database and the Web (4)
ECON 381 Research Methods in Economics (4)
ECON 382 Economic Forecasting (3)
ECON 485 Economics Research Seminar (3)
GEOG 320 Principles of GIS with Lab (3)
MATH 132 Calculus II (4)
MATH 240 Linear Algebra (4)
POLS 489 Capstone Seminar (4)
SOC 350 Methods of Social Research (4)
Notes regarding prerequisites:
COSC 110 is a prerequisite for DATA 210
DATA 310 requires second-year standing
COSC 110 and MATH 131 are prerequisites for DATA 440