Artificial Intelligence and Machine Learning

Catalog description

This course is intended to explore the concepts and algorithms in the development of modern artificial intelligence applications. The course also provides foundational knowledge of machine learning algorithms and tools. Topics covered include: the principles of supervised and reinforcement learning, the K nearest neighbor method, linear regression and other modeling and analysis tools. By the end of the course, students will learn the principles and tools that enable them to design and develop intelligent systems and use ML libraries for AI programming. Prerequisite: CSC 2054 and MAT 1014 (or MAT 1015)