DSAN 675 - Programming for Data Science

This course will cover practical coding skills to enable students to utilize coding tools and techniques to do analysis in a big data environment. This class covers coding techniques such as loops, if statements, nested statements, and customized functions, etc. Students can use coding techniques to conduct data description, probability distributions analysis, statistical inference, association analysis and multiple linear regression, and supervised and unsupervised techniques. Typically offered Fall, Spring, Summer.
Level: GR
Credit Hours: 3

Ferris Equivalencies:

Department: MKTG