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Neural Networks: Zero to Hero

Build neural networks from scratch in code, with Andrej Karpathy.

4.5(4.4k)441.7K learners EN
ANCreated by Andrej Karpathy

19h 29m

On-demand video

13

Lessons

Included

Certificate

Mobile & TV

Watch anywhere

You'll use
OpenAITensorFlow
Neural Networks: Zero to Hero
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This course includes:

  • 19h 29m on-demand video (free)
  • 13 lessons
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion

What you'll learn

  • Build and train neural nets from first principles
  • Implement backpropagation by hand (micrograd)
  • Code a GPT-style language model from scratch
  • Truly understand what happens inside an LLM

Official study guide

The complete 28-page companion book for Neural Networks: Zero to Hero, covering every module with worked examples, key terms, self-check questions, and a full glossary. Print it or read it offline.

Tools & technologies

Industry-standard tools you'll work with in this course.

OpenAITensorFlow

Course content

3 sections · 13 lessons · 19h 29m

  • The spelled-out intro to neural networks and backpropagation: building microgradPreview2h 25m
  • The spelled-out intro to language modeling: building makemore1h 57m
  • Building makemore Part 2: MLP1h 15m
  • Building makemore Part 3: Activations & Gradients, BatchNorm1h 55m
  • Building makemore Part 4: Becoming a Backprop Ninja1h 55m
  • Building makemore Part 5: Building a WaveNet56m
  • Let's build GPT: from scratch, in code, spelled out.1h 56m
  • State of GPT | BRK216HFS42m
  • Let's build the GPT Tokenizer2h 13m
  • Let's reproduce GPT-2 (124M)4h 1m

Requirements

  • •Solid Python
  • •Basic calculus
  • •Some ML helps

About this course

Build neural networks from scratch in code, with Andrej Karpathy. This curated learning path is organized into 3 modules and 13 lessons, taught by Andrej Karpathy. MegaCourse upgrades the original 1-section playlist into a complete mega course by adding 2 curated reading & resource lessons, a final knowledge-check quiz, plus structure, learning outcomes, progress tracking, and a shareable certificate of completion.

Who this course is for

  • ML engineers
  • Serious self-learners

Instructor

AN
Andrej Karpathy

Trusted creator on MegaCourse

Licensing & attribution

License: YouTube Standard License

Videos are embedded from their original creators and remain free to watch. MegaCourse's paid layer covers our own study guides, graded exams, certificates, and curation.

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