Minor in Data Science

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The minor in data science is intended to provide students in STEM and other quantitative disciplines (for example, economics or psychology) with the basic tools to analyze and manipulate complex data in order to extract meaningful information and to make data-based decisions.

18 Credits Required

Requirements: 

DSC 100 - Data Science I
DSC 101 - Data Science II

Completion of 12 additional credits selected from the following list of possible classes. At least one class from each list must be selected:

Math classes:
MAT 150 - Calculus I (4cr)
MAT 151 - Calculus II (4cr)
MAT 178 - Elementary Discrete Mathematics (3cr) 
MAT 221 - Intermediate Applied Statistics (4cr)
MAT 326 - Regression Analysis(3cr)  
MAT 328 - Time Series Analysis (3cr) 
MAT 329 - Bayesian Analysis and Decision Making (3cr) 
MAT 372 - Linear Algebra (3cr)  
MAT 429 - Modern Nonparametric Statistics (3cr) 
MAT 428 - Mathematical Foundations of Machine Learning (3cr) 

Computer science classes:
CSC 212 - Data Structures (3cr) 
CSC 229 - Object Oriented Programming (3cr) 
CSC 235 - Web and Database Development (3cr) 
CSC 321 - Algorithm Design and Analysis (3cr) 
CSC 330 - Software Design and Development (3cr) 
CSC 335 - Database Systems (3cr) 
CSC 463 - Development of Distributed and Ecommerce Applications (3cr) 
CSC 477 - Data Mining (3cr) 
CSC 481 - Artificial Intelligence(3cr)  

*Only one of MAT 428 or CSC 481 can be applied to the minor.