DATA 101 Fundamentals of Data Science

Understandable introduction to the field of data science.  Topics include the data science methodology, data preparation, exploratory data analysis, a classification algorithm, the model building process, and model evaluation.  Topics may include decision trees and report writing.  Students will gain familiarity with a widespread open-source data science platform, such as R.

Credits

4

Prerequisite

B or better in a first semester statistics course, such as STAT 104 or STAT 200 or STAT 215 or permission of department chair.

General Education

Offered

  • Fall and Spring