Students will be introduced to concepts related to data collection, data quality, data analysis and modeling, as well as data visualization, through the context of sports analytics. Data and analytics have been part of the sports industry dating to the 1870s, when the first boxscore in baseball was recorded. Recently, advanced data mining and machine learning techniques have been incorporated into the operations of sports franchises. In this course, students will become familiar with data science concepts and data analysis techniques, the interpretation and use of probabilities, the notion of overfitting and how to avoid it, and the components of a useful visualization.

Academic Career: Undergraduate
Course Component: Lecture
Grade Component: LG/SNC Elective Basis
Minimum Credits: 3
Maximum Credits: 3