Foundations of Data Science

Catalog description

This course is an introduction to the data science workflow covering project formulation, data pre-processing, algorithm application, and result interpretation. Students learn to select and apply appropriate data science techniques, differentiate between supervised and unsupervised problems, and process incomplete datasets for analysis. The course emphasizes comparing model performance and communicating methods and results effectively to both technical and non-technical audiences. Prerequisite: STAT 145 or STAT 245 ; MTH 160 or MTH 175 or MTH 207 . Offered Fall, Spring.