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Natural Language Processing with Deep Learning (CS224N)

Natural Language Processing with Deep Learning (CS224N) on Stanford Online is a ten-week graduate course on the algorithms and neural networks behind language understanding, from word-level and syntactic processing to question answering and machine translation.

Open at Stanford University ↗Common questions

Who it suits

  • People with a machine learning or AI foundation who want to build and extend neural models for language tasks.
  • Engineers who want a final project applying a complex model to a large-scale NLP problem.

What it covers

  • The computational properties of natural languages and how linguistic information is processed.
  • Syntactic and semantic processing, coreference, question answering and machine translation.
  • Implementing, training, debugging and extending neural network models for language understanding.
  • A final project applying a complex neural network model to a large-scale NLP problem.

Watch here

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  • Stanford Online · 2021

    Stanford CS224N: NLP with Deep Learning | Winter 2021 | Lecture 1 - Intro & Word Vectors

    Open on YouTube

Before you start

  • Stanford lists a conferred bachelor’s degree with an undergraduate GPA of 3.0 or better.
  • Calculus and linear algebra.
  • One of: an introduction to natural language processing (CS124), an introduction to artificial intelligence (CS221) or machine learning (CS229).

Common questions about Natural Language Processing with Deep Learning (CS224N)

How long is it?
Stanford lists 10 weeks at 10 to 20 hours a week, and 4 academic units.
What should I know first?
Calculus, linear algebra, and one of CS124, CS221 or CS229, as Stanford lists.
Can I enrol any time?
Enrolment is only open during set periods, and an application is needed for graduate courses, so check the page for the current dates.

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Where this comes from

Written from Stanford University’s own pages, read on 2026-10-13. Content, prices and availability change, so the provider’s page is the source. We are not affiliated with Stanford University and this is not an endorsement.