- CS 660/585 Sequential Decision Making: Many of the most interesting problems are sequential decision making problems! In this class, we cover basic and advanced techniques for solving these problems such as: adversarial search, Monte-Carlo tree search, and reinforcement learning. Now open to undergraduate students!
- CS 463G Introduction to Artificial Intelligence: In this class you’ll learn everything you’ve ever wanted to know about artificial intelligence but have been too afraid to ask! Meant to provide a broad overview of AI topics including search, constraint satisfaction, logic, and probabilistic reasoning.
- CS 660 Sequential Decision Making
- CS 460G Introduction to Machine Learning: Learn how to create descriptive and predictive computational models using large (but not big necessarily) amounts of data! In this class you will be introduced to various supervised and unsupervised learning techniques including decision trees, neural networks, and clustering.
- CS 660/585 Interactive Machine Learning: While there have been many advances in machine learning, there are still many problems that are too large for machine learning to solve in a reasonable amount of time. One way to improve these methods is to augment machine intelligence with human intelligence. In this class, you’ll be introduced to the state of the art in interactive machine learning through reading papers and actively working on a research project of your own choosing.