Spring 26 CSCI 5525 Advanced Machine Learning

Instructor: Zirui “Ray” Liu

Time: Spring 2026, Tues/Thurs 11:15 AM - 12:30 PM

TA: Hao Li

Location: Keller Hall 3-230

Course Description

The course is organized into three parts. In Supervised Learning, we will learn popular ML methods ranging from linear regression, boosting trees, to deep neural networks, and the Transformer architecture that powers modern AI. In Unsupervised Learning, we will learn how machines generate content through autoregressive modeling, Variational Autoencoders, and Diffusion models, which are the engines behind today’s text, image and video generation systems. In Reinforcement Learning, we will learn how AI agents make decisions through policy gradients and Proximal Policy Optimization, the same techniques used to train ChatGPT and create game-playing AI.

Course Schedule (tentative)

The course schedule may be changed.