200
This course covers web scraping, recommender systems, dimensionality reduction techniques, and machine learning models for regression, classification, and clustering. Emphasis is placed on hands-on projects and case studies to apply these concepts in real-world scenarios while elevating ethics, visuals, and data handling from the introductory course.
Credit Hours: 4
Prerequisites
CSC 102 with a C or higher,
DSC 101 with a C or higher,
MAT 272 with a C or higher