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CS224n: Natural Language Processing with Deep Learning

4.9(7,000) on Stanford Online·1.2M enrolled
Advanced 50 hours EnglishFREE
Our recommendation
Stanford's leading course on natural language processing with deep learning, and one of the best places to understand the models behind modern language AI, including transformers. The lectures and assignments are free online. It is advanced and maths-heavy, with no certificate from the free materials.

Good for: Learners with machine-learning basics who want to understand modern NLP and transformers deeply.

Less suitable if: You are new to machine learning, or you only want to use language models rather than understand them.

Skills you'll gain

Natural language processingDeep learningTransformersWord embeddingsLanguage modelsPyTorch

Is this course right for you?

A good fit if you…

You know Python and machine-learning basics
You want to understand transformers and language models
You can handle demanding assignments

Consider something else if you…

You are new to machine learning
You only want to use LLMs, not build them
You need a certificate

Requirements: Python, calculus, linear algebra and machine-learning basics. Advanced.

Realistic time: About 50 hours of lectures, plus substantial assignments.

About this course

CS224n is Stanford's NLP with deep learning course and arguably the most important academic resource for understanding how modern language models work. Taught by Christopher Manning — one of the foremost NLP researchers in the world — it covers word vectors (Word2Vec, GloVe), recurrent neural networks, sequence-to-sequence models, attention mechanisms, the Transformer architecture that underpins every modern LLM, BERT, GPT, and the current landscape of large language models.

What you'll learn

Understand word vectors and their mathematical foundations
Implement and understand recurrent neural networks for sequence tasks
Build and understand the Transformer architecture from first principles
Understand BERT, GPT, and how pre-training and fine-tuning work
Apply NLP models to tasks including classification, translation, and QA

This course includes

50h
On-demand video
Yes
Mobile access
English
Language

What it costs

The lectures and assignments are free and public on the course website. There is no certificate from the free materials.

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Instructor

CM
Christopher Manning
Stanford Online instructor
1.2M+ learners5 courses4.9 instructor rating

Taught by Christopher Manning, Thomas M. Siebel Professor in Machine Learning at Stanford and co-author of foundational NLP textbooks including 'Foundations of Statistical Natural Language Processing.'

About this provider

SO
Stanford Online
Stanford University's online learning platform offering free and paid courses from Stanford faculty across AI, ML, medicine, and computer science.
Visit Stanford Online

Frequently asked questions

Yes. It is one of the best courses for understanding the architecture behind modern language models, including transformers.
Yes. The lectures and assignments are public on the course website.
Python, some calculus and linear algebra, and machine-learning basics. It is advanced.
No. The materials are open, but there is no certificate.
For a deep understanding of how language models work, it is among the best resources available.
Free
to audit
Enroll now