Undergraduate Prerequisites: DS210 or equivalent, DS320 or equivalent, DS 340 or equivalent - Spring 2024: A Section - This course introduces students to the field of Reinforcement Learning (RL). We will cover (1) the basic concepts in r. and (3) modern challenges (exploration, partial observability, multi-agent RL). B Section - In this course students will gain an understanding of the fundamentals in Deep Learning and then apply those concepts in exercises and applications in python. You'll learn the foundations of training and inference, then become familiar with canonical network architectures including convolutional neural networks and transformers. We'll look at generative pre- trained Transformer models and pros and cons of prompt engineering versus finetuning. Finally, students will be able to apply many of the techniques they learned in a final class project.

Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.