CS224N: NLP with Deep Learning
by Stanford University
Stanford's flagship NLP course — word vectors to transformers and LLMs, with rigor.
Overview
CS224N is the academic gold standard for natural language processing with deep learning. It progresses from word vectors and RNNs to attention, transformers, pretraining, and modern LLMs, with mathematically rigorous lectures and substantial coding assignments. Lecture videos, slides, and notes are freely available online. Choose it when you want research-grade depth on how language models are built and trained.
At a Glance
- Topic
- Models
- Level
- Advanced
- Format
- Course
- Cost
- Free
- Duration
- Full university course
- Provider
- Stanford University
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓Word embeddings and sequence models
- ✓Attention and the transformer architecture
- ✓Pretraining and modern LLMs
- ✓NLP tasks and evaluation
Highlights
- •Stanford graduate-level rigor
- •Free lectures, slides, and assignments
Who It’s For
Best For
- ✓Learners wanting deep, research-grade NLP knowledge
Prerequisites
- •Python
- •Calculus/linear algebra
- •ML basics
FAQ
What is CS224N: NLP with Deep Learning?
Materials and recorded lectures for Stanford's graduate NLP course covering embeddings, attention, transformers, and large language models.
Is CS224N: NLP with Deep Learning free?
CS224N: NLP with Deep Learning is free to access.
What level is CS224N: NLP with Deep Learning for?
CS224N: NLP with Deep Learning is aimed at a advanced audience. Recommended background: Python, Calculus/linear algebra, ML basics.
How long does CS224N: NLP with Deep Learning take?
Expect roughly Full university course. Most learners work through it at their own pace.
What will I learn from CS224N: NLP with Deep Learning?
You'll learn: Word embeddings and sequence models; Attention and the transformer architecture; Pretraining and modern LLMs; NLP tasks and evaluation.