Description
This course provides an in-depth study of data mining principles and techniques. Students will learn how to discover patterns and extract actionable insights from large data sets. Core topics include data preprocessing, classification, clustering, association rule mining, anomaly detection, and the ethical considerations of data mining. The course will include practical applications in business, healthcare, and social sciences, using industry-standard tools. Upon completion, students should be able to identify appropriate data mining techniques for various data types, implement and evaluate models, and communicate findings effectively. Prerequisite: MAT 141 or CSC 130