Fundamentals and Principles of Data Science. 3 credits, 3 contact hours

Catalog description

Prerequisites: CS 114 and ( MATH 333 or MATH 341 ) with a grade C or better. Fundamentals and principles of data science familiarize students with the theories and techniques for data representation, manipulation, analysis, visualization, and interpretation. Topics include introduction to data preparation and preprocessing, data mining, anomaly detection, machine learning, statistical learning, data analysis and visualization, large language models, ethics, and popular data science tools and systems. Hands-on work will include Python with Pandas coding.