Artificial Intelligence and Deep Learning

1 Unit · Graduate

This course introduces the field of artificial intelligence from its origins with logic programming to contemporary deep learning models. It illustrates generative, probability-rule-based models as well as discriminative models for learning from data. It reviews applications of artificial intelligence and deep learning in vision and language processing. Students learn best practices for building deep learning models for classification and regression. They learn about feature engineering, autoencoders, and strategies of unsupervised and semi-supervised learning, as well as reinforcement learning. This is a project-based course with extensive programming assignments.