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 begin with foundational concepts such as word representations, and moving through neural approaches like recurrent networks and attention mechanisms. From there, we explore modern Transformer-based architectures and conclude with recent advances in the field, such as retrieval-augmented models, mixture-of-experts, AI agents, and more.
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.
Schedule (Tentative)
All deadlines are at 5:59 PM PST.
- 01/20 Tue
- Introduction
- 01/22 Thu
- Word representation & Text classification
- 01/27 Tue
- Language modeling basics
- Assignment 1 released
- 01/29 Thu
- Recurrent models & Attention
- 02/03 Tue
- NLP task case study: Text generation
- 02/05 Thu
- NLP task case study: Question answering
- 02/10 Tue
- LLM basics: Architecture (Tokenizer, Transformers, Encoders, Decoders)
- Assignment 1 due Team matching survey due Assignment 2 released
- 02/12 Thu
- LLM basics: Training (Pre-training, Fine-tuning)
- 02/17 Tue
- LLM basics: GPT-3, Prompting, In-context learning
- 02/19 Thu
- Pre-training deep dive: Scaling laws
- 02/24 Tue
- Pre-training deep dive: Data curation
- Assignment 2 due
- 02/26 Thu
- Experimental design & Human annotation
- 03/03 Tue
- Architecture deep dive: Retrieval and RAG
- Project abstract due Assignment 3 released
- 03/05 Thu
- Architecture deep dive: Mixture-of-Experts
- 03/10 Tue
- Post-training
- 03/12 Thu
- Inference methods & Evaluation
- 03/17 Tue
- Guest lecture (TBA)
- Assignment 3 early milestone due
- 03/19 Thu
- Test-time compute & Reasoning models
- Assignment 3 due
- 03/24 Tue
- No class: Spring break
- 03/26 Thu
- No class: Spring break
- 03/31 Tue
- LLM agents
- Assignment 4 released
- 04/02 Thu
- Vision-language models
- 04/07 Tue
- Speech models
- 04/09 Thu
- Interactive embodied agents
- 04/14 Tue
- Pragmatics
- Assignment 4 early milestone
- 04/16 Thu
- Impact & Social implications
- Assignment 4 due
- 04/21 Tue
- Guest lecture (TBA)
- 04/23 Thu
- Guest lecture (TBA)
- 04/28 Tue
- Project presentation
- 04/30 Thu
- Project presentation
- Project report due by 05/07 (Thu)