GE220: Foundations of Artificial Intelligence in Engineering

This course introduces fundamental principles and applications of machine learning for engineering students. It covers key supervised and unsupervised algorithms such as Bayesian learning, classification, regression, dimensionality reduction, neural networks, and deep learning. The course further explores industrial data analytics, fault detection, and optimization techniques, with a focus on solving real-world engineering problems. Students will gain both theoretical understanding and hands-on experience with modern machine learning tools and software.