fast.ai

Practical Deep Learning for Coders is the entry point, and it stays free. That's the deal. The 2022 edition recorded at the University of Queensland packs 9 lessons of about 90 minutes each, covering computer vision, NLP, tabular analysis, and collaborative filtering. You learn PyTorch, fastai, Hugging Face Transformers, and Gradio along the way, all on free cloud notebooks. The prerequisite bar is deliberately low. Some coding experience, no university math. That's it. It's a solid place to learn deep learning without paying tuition.

fastai is a Python library that wraps PyTorch in higher-level building blocks. It handles the repetitive parts of a training pipeline, like data loading, augmentation, and learning rate schedules, so you can get strong results without writing hundreds of lines of setup code. The library is layered by design, which means you can call one function for a standard task or drop down to raw PyTorch when you need custom control. It's open source and free to use in your own projects. No license fees, no strings.

The advanced course picks up where part 1 ends and rebuilds the machinery from scratch, including a full training loop and stochastic gradient descent. The 2023 edition added more than 30 hours of video, spanning topics like diffusion models and the techniques behind Stable Diffusion. This is where the course stops hiding complexity, and it's aimed at people who finished part 1 and want to understand why things work, not just how to call them. Expect a grind.

Deep Learning for Coders with fastai and PyTorch is the companion text, and every chapter is readable free online. Each chapter also exists as a runnable Jupyter Notebook, so you can edit the code and see what changes instead of reading passive examples. That matters more than it sounds. The book drew praise from Google's research director Peter Norvig, who called it one of the best sources for a programmer to become proficient in deep learning.

forums.fast.ai is the support layer that keeps the whole thing usable. Years of threads cover everything from CUDA errors to project feedback, and the community runs a Show Your Work section where students post their models. That's where you find out whether someone else already hit your problem. The course site collects alumni stories too, including people who placed in machine learning competitions or landed roles at major labs after finishing.

Since joining Answer.AI, fast.ai has been building a different kind of course. How To Solve It With Code teaches a method the team calls Dialog Engineering, where you work with an AI partner in small steps instead of generating a whole codebase at once. Small moves, better code. The 10-lesson program stretches beyond coding into writing, reading papers, web APIs, and system administration. It's a paid, cohort-based experience with a live Discord, and it's the clearest signal of where the organization is heading.