Advanced Natural Language Processing

Spring 2026

Instructor: Sewon Min, Alane Suhr
Class hours: TuThu 15:30–17:00 (15:40–17:00 considering Berkeley time)
Class location: SODA 306
Contact: TBA
Ed link: TBA

If you are interested in taking the course and can’t directly enroll, please submit this form.

This course provides a graduate-level introduction to Natural Language Processing (NLP). We will survey foundational approaches such as word representations and n-gram language models, followed by neural methods including recurrent networks and attention mechanisms, and then progress to modern Transformer-based architectures. In addition, the course will cover advanced topics in contemporary NLP such as retrieval-augmented models, mixture-of-experts architectures, AI agents, and vision-language models.

Prerequisites: CS 288 assumes prior experience in machine learning and proficiency in PyTorch. Students should be familiar with neural networks, PyTorch, and NumPy; no introductory tutorials will be provided. Relevant experience can be gained in CS 182, 188, or 189. Prior coursework in linguistics or NLP (e.g., CS 183/283A) is recommended but not required.

Schedule (Tentative)

All deadlines are by 6PM PST.