PyTorch
PyTorch is an open-source deep learning framework developed by Meta AI that uses dynamic computation graphs, making it intuitive to write and debug neural networks in Python. It provides a flexible tensor library with GPU acceleration and a rich ecosystem of tools for training, evaluating, and deploying models. PyTorch has become the dominant framework for research and is rapidly expanding into production use cases through features like torch.compile and TorchServe.
PyTorch is now the primary framework required in AI/ML job postings at leading labs, startups, and enterprise AI teams, having overtaken TensorFlow in academic and industry adoption. Companies hiring ML engineers, research scientists, and AI platform engineers almost universally list PyTorch proficiency as a required skill. The release of PyTorch 2 with torch.compile brought compiler-level performance improvements that make the framework viable at scale without sacrificing the flexibility researchers depend on.
🎓 Courses
Practical Deep Learning for Coders
by Jeremy Howard
Free, code-first course that has been viewed over 6 million times. Teaches PyTorch alongside fastai and Hugging Face Transformers through real projects, with no university math prerequisites. The gold standard for hands-on PyTorch learning.
PyTorch for Deep Learning Professional Certificate
by Laurence Moroney
Three-course structured path from tensors and basic neural networks through CNNs, NLP with Hugging Face, Siamese networks, and model deployment via ONNX and MLflow. Ideal for learners who prefer a certificate-driven progression.
Zero to Mastery Learn PyTorch for Deep Learning
by Daniel Bourke
Free, open-source course with 25+ hours of material on YouTube. Covers PyTorch fundamentals, computer vision, NLP, and transfer learning in a code-first style with all notebooks publicly available on GitHub.
Deep Learning with PyTorch
by IBM Skills Network
Covers shallow and deep neural networks, convolutional networks, batch normalization, and dropout with hands-on labs. Part of the IBM Deep Learning Professional Certificate and can be audited for free.
Learn the Basics — Official PyTorch Tutorials
by PyTorch Team (Meta / Linux Foundation)
The official starting point maintained by the PyTorch core team. Covers tensors, datasets, data loaders, autograd, model building, and training loops. Always up to date with the latest PyTorch release (2.12 as of 2025).
📖 Books
Deep Learning with PyTorch, Second Edition
Luca Antiga, Eli Stevens, Howard Huang, Thomas Viehmann · 2025
The canonical PyTorch book, fully updated by PyTorch core developer Howard Huang. Covers CNNs, RNNs, Transformers, generative AI, and diffusion models with hands-on projects. The second edition adds coverage of LLMs and modern generative architectures missing from the first edition.
Hands-On Machine Learning with Scikit-Learn and PyTorch
Aurélien Géron · 2024
Géron's acclaimed hands-on series updated for PyTorch, covering classical ML through advanced deep learning including transformers, diffusion models, fine-tuning LLMs, and reinforcement learning. Leverages the Hugging Face ecosystem throughout.
AI and ML for Coders in PyTorch
Laurence Moroney · 2025
444-page O'Reilly book focused on practical model building for computer vision, NLP, and sequence modeling with PyTorch, plus generative AI with Hugging Face Diffusers. Ideal companion to Moroney's Coursera certificate for readers who prefer books.
🛠️ Tutorials & Guides
PyTorch in One Hour: From Tensors to Training Neural Networks on Multiple GPUs
A dense, practical walkthrough by Sebastian Raschka (author of 'Machine Learning with PyTorch and Scikit-Learn') covering everything from tensor basics to multi-GPU training in a single session. Well-regarded by practitioners for its clarity and depth-per-minute ratio.
Learn the Basics — Official PyTorch Tutorials
The official beginner tutorial from the PyTorch core team covers the full ML workflow: data loading, model definition, autograd, optimization, and model persistence. Always synchronized with the current stable release.
PyTorch Tutorial for Deep Learning Researchers
A widely-starred community GitHub repository covering basics, intermediate topics (CNNs, RNNs, BiLSTMs), and advanced patterns. Useful as a quick-reference code library when moving from tutorial to real projects.
🏅 Certifications
PyTorch for Deep Learning Professional Certificate
DeepLearning.AI / Coursera · Included in Coursera subscription (~$49/month) or financial aid available
One of the few PyTorch-specific certificates from a well-recognized AI education provider. Covers the full stack from fundamentals to deployment and is recognized by hiring managers at technology companies.
Learning resources last updated: June 18, 2026