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ISA 330. Programming for Analytics. 3 Credit Hours.

This course introduces students to common programming tools used for Data Science application development. Data analysts often implement their solutions using programming languages such as R and Python. Because of this, it is critical that the data analyst be comfortable in such development environments and be able to understand when a solution needs to be programmatically developed. The course covers hands-on programming techniques for analytics which includes web scraping and other data extraction techniques, data transformation, data staging, data analysis, and finally data presentation and visualization. The course will give the students the confidence they will need to consider themselves programmers and to understand the types of analytics solutions that can be assisted or obtained through programming techniques.
Prerequisites: ISA 221 or ISA 341 or AA 304 or permission of the instructor
Session Cycle: Spring
Yearly Cycle: Annual.