ENES260

This introductory course covers a wide range of topics, from the fundamentals of linear algebra and programming to advanced topics such as backpropagation in neural networks and hardware considerations for Large Language Models. This course will explore how professionals use Machine Learning (ML) to solve real-world engineering problems and even implement models in a team-based project. This course also delves into unsupervised algorithms for dimensionality reduction, defensive strategies against adversarial attacks on ML, ethical considerations of the open internet, and copyright.