CIS 2640 — Introduction to Machine Learning (ML) 4 Credit Hours
This course introduces students to Machine Learning (ML) which is a sub-field of Artificial Intelligence (AI) that uses big data. Discusses classic unsupervised, supervised, and reinforcement learning methods used in the field of data classification, clustering, and optimization. This includes k-means, hierarchical clustering, self-organizing maps, linear regression, decision trees, Naïve Bayes, and optimization techniques such as genetic algorithms. It will also cover accessing interesting datasets, ideas on how to collect data from users, and many different ways to analyze and understand the data once found. (3 lecture hours, 2 lab hours)