CT 6915 - Machine Learning for Data Science and Analytics

This course covers various non-linear algorithms necessary to perform both supervised and unsupervised learning analysis for modern business analytics problems. The emphasis is on application of ML through case studies from industries such as aviation, sports, healthcare and banking. Various topics covering prediction problems related to classification and regression, partitioning techniques, clustering and dimension reduction will be discussed. Python will be used throughout the course. Credits: 4 Students cannot take both CT 6910 Machine Learning and CT 6915 Machine Learning for Data Science and Analytics for credit.