Scientific Foundation of Machine Learning. 3 credits, 3 contact hours

Catalog description

Prerequisites: ( CS 100 or DS 100 ) and ( CS 375 or CS 370 ). This course provides an advanced exploration of machine learning, emphasizing its mathematical foundations and the interplay between statistical and computational aspects. Designed for students seeking to deepen their understanding or advance the theory and development of learning algorithms, the course primarily focuses on conceptual insights at the undergraduate level. Key topics include classical results in statistical and computational learning theory, recent advances in deep learning, unsupervised learning, and large language models (LLMs). Students will acquire tools to analyze and prove performance guarantees for learning methods, fostering a strong theoretical foundation and practical expertise in machine learning.