Machine Learning

Catalog description

This course examines the concepts, principles, and application of machine learning (ML), the major driving force of current AI development. This course provides fundamental knowledge of ML and hands-on experiences to develop ML models in real-world scenarios. The topics of this course include supervised learning, unsupervised learning, classification, and regression. This course will introduce a wide range of ML algorithms, such as K-Nearest Neighbor, K-Means Clustering, Logistic Regression, Principal Component Analysis, and Neural Networks. TSI Restriction(s): Reading, Writing, and Math