On 2026-10-08 course.fast.ai is live and free with all 2022 Part 1 lessons and Part 2 lessons available on demand; no new Practical Deep Learning version has been released since 2022, and fast.ai's newer work is a separate paid course, 'How to Solve It With Code', run with Answer.AI. source
A free, self-paced deep learning course built on PyTorch and the fastai library, taught top-down from working models to theory, with a free companion book and forums. It suits working programmers who want practical deep learning without paying, and it offers no certificate, cohort or job support. Before committing, check that you are comfortable with the 2022-era material and the Jupyter notebook workflow, since no 2025 or 2026 refresh of this course exists.
The facts
| Category | AI and machine learning |
|---|---|
| Website | course.fast.ai |
| Based | Remote · founded 2016 |
| Format | online-self-paced |
| Programs | Practical Deep Learning for Coders Part 1 (2022), Part 2: From Deep Learning Foundations to Stable Diffusion, How to Solve It With Code (separate, with Answer.AI) |
| Length | Self-paced. Part 1: 9 lessons of about 90 minutes each; Part 2: 17 lessons plus 2 bonus lessons, over 30 hours of video (course.fast.ai). unknown |
| Tuition | $0 Completely free, including the companion book and forums (course.fast.ai). The separate 'How to Solve It With Code' course does not publish a price on fast.ai's announcement pages; it mentions a refund available until 2 weeks into the course. verified |
| Financing | free Free; no enrollment, no certificate, no job guarantee. fast.ai is a nonprofit founded by Jeremy Howard and Rachel Thomas (Wikipedia, fast.ai/about). |
| Admission | open Prerequisite is a year of coding experience, Python preferred (course.fast.ai). Part 2 assumes Part 1 or equivalent PyTorch, NLP and computer vision experience. |
| Stack | Python, PyTorch, fastai, Hugging Face Transformers, Gradio, Stable Diffusion, DDPM/DDIM |
Outcomes
This program does not publish job-placement or salary outcomes. Treat any number you hear from admissions as unverifiable.
Interview-prep depth
0 / 5
Public lesson list covers deep learning practice only; nothing on interviews, DS&A, system design or behavioral prep.
Whatever the program covers, the interview itself is free to prepare for here: coding patterns, system design, practice prompts, company guides.
What a careful reader should know
Founded October 2016 by Jeremy Howard and Rachel Thomas as a nonprofit (Wikipedia). The current Practical Deep Learning for Coders is the 2022 edition (Part 1 recorded at the University of Queensland; Part 2 repo is 'course22'). fast.ai's November 7, 2024 post says the group had not released a new course in over two years and announced 'How To Solve It With Code' (taught by Jeremy Howard, Johno Whitaker and Audrey Roy Greenfeld, later with Eric Ries), which is a different, dialog-engineering-focused course rather than an update of the deep learning material; an October 15, 2025 post says that course is now available with a new run starting November 3, 2025 and does not list a price on the fast.ai page. The fast.ai blog's 2025-2026 posts are essays by Rachel Thomas, not course updates. Reddit threads in r/learnmachinelearning still recommend the course and organise study groups; the main complaints are the notebook-heavy format being confusing for beginners and the 2022 material predating the LLM-era tooling. Course Report has no page for fast.ai.
Third-party signals: Reddit sentiment positive. Graduation-time star ratings are collected by the schools; weigh them accordingly.
Sources (7)
This directory takes no lead fees or placement payments from any program. Where a program runs an affiliate scheme we say so on its page and mark the link. Facts carry a badge: verified means we read it on a primary source on the date shown, reported means a third party said it, unknown means nobody we trust has published it.
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