Free practical deep learning courses, research and open-source libraries
Estimated monthly website visits
Similarweb estimates for this domain, not active users. Only available observation months are shown; collection date is separate from the traffic period.
Collected Nov 11, 2026
This is our editors' assessment out of 5, not an average of user ratings. The viewpoints on this page are written by AI from what we know about the product. They are not customer reviews.
According to OpenAITools.app telemetry verified on 2026-11-11, fast.ai (fast.ai) is an AI platform indexed under AI Course generating 250.72K monthly visits with a month-over-month traffic delta of -29.13K (-10.4%). Its primary geographic market is United States (24% traffic share), and it operates on a Free pricing model. Top competing alternatives by monthly volume include DeepLearning.AI (2.56M visits/mo), The Full Stack (fullstackdeeplearning.com) (46.08K visits/mo), Open Data Science (ODS.ai) (159.63K visits/mo).
Best deep learning course ever created. Period.
Fastai library makes PyTorch boilerplate vanish.
Practical from day one without losing depth.
Some notebooks need minor updates for newer PyTorch versions.
AI-synthesized perspectives grounded in live site inspection, pricing structure, and category benchmarks — presented as editorial viewpoints rather than individual customer testimonials.
A free, top-down course that gets you training real models immediately and explains the theory as you go, with notebooks and video lessons.
A newer educational format that teaches iterative, exploration-driven problem solving with an interactive platform, replacing the classic course structure.
A high-level API that makes modern deep learning techniques concise and accessible while staying flexible for research work.
Develop, test, document and publish complete Python packages directly from Jupyter notebooks, ending the notebook-versus-git conflict.
Long-form articles on AI in society, education, ethics, technical deep dives and attitudes, plus an active community forum.
fast.ai began with a simple premise: deep learning should be taught top-down, starting with working code that produces results on day one, and only then unpacking the theory. That approach produced Practical Deep Learning for Coders, one of the most widely followed free courses in the field, aimed at people with programming experience rather than advanced mathematics. Later offerings include From Deep Learning Foundations to Stable Diffusion and the newer How to Solve It With Code, which replaced the traditional course format with a problem-solving platform.
Software is the second pillar. The fastai library layers a high-level, opinionated API on top of PyTorch so that training state-of-the-art models takes a handful of lines, while remaining flexible enough for research. nbdev lets teams develop, document and publish entire Python packages from inside Jupyter notebooks, solving the long-standing friction between notebooks and version control. Both projects are open source and supported by an active community forum and documentation.
Alongside teaching and tooling, fast.ai publishes widely read writing on the societal side of AI, including critiques of how AI power concentrates, debates about AI safety framing, and analysis of education and technology. In late 2024 the organisation announced it was joining Answer.AI, a new kind of R&D lab focused on building practical end-user products from foundational research, while the fast.ai blog and course materials remain freely available.
Programmers with no machine learning background can start building and deploying models on day one, then fill in the mathematics.
Use the fastai library to prototype vision, text and tabular models quickly, or nbdev to turn notebooks into maintained packages.
Instructors can base university, bootcamp or internal training programmes on openly available notebooks, videos and documentation.
Follow critical, well-cited commentary on AI ethics, power concentration, education and the realities behind AI hype.
Side-by-side telemetry comparison of competing AI tools in the same primary category
| Rank | AI Tool | Monthly Visits | MoM Growth | Direct traffic share | Pricing | Head-to-Head |
|---|---|---|---|---|---|---|
| ● | fast.ai | 250.72K | -10.4% | 55% direct | Free | Current |
| 1 | DeepLearning.AI Offers broad structured courses by Andrew Ng, but lacks fast.ai's deep hands-on focus on PyTorch code. | 2.56M | -7.2% | 53% direct | Freemium | vs DeepLearning.AI |
| 2 | The Full Stack (fullstackdeeplearning.com) Provides practical production machine learning tutorials, but covers broader deployment stacks rather than pure deep learning foundations. | 46.08K | +6.6% | 57% direct | Free (educational content) | vs The Full Stack (fullstackdeeplearning.com) |
| 3 | Open Data Science (ODS.ai) A vibrant open community for data science practitioners, though it operates as a network rather than structured courses. | 159.63K | +15.9% | 69% direct | Free | vs Open Data Science (ODS.ai) |
| 4 | LAION Publishes open-source datasets and research models, but focuses on raw AI research rather than structured educational tutorials. | 18.49K | -24.1% | 28% direct | Free | vs LAION |
| 5 | LabLab.ai Hosts hands-on AI hackathons and developer tutorials, but emphasizes rapid prototyping over deep academic machine learning. | 431.53K | -39.7% | 47% direct | Free | vs LabLab.ai |
| 6 | Learn Prompting Offers free educational guides on prompt engineering, but focuses on LLM usage rather than training neural networks. | 159.81K | -8.6% | 42% direct | Freemium, Free Trial, Contact for Pricing | vs Learn Prompting |
Offers broad structured courses by Andrew Ng, but lacks fast.ai's deep hands-on focus on PyTorch code.
Offers broad structured courses by Andrew Ng, but lacks fast.ai's deep hands-on focus on PyTorch code.
Provides practical production machine learning tutorials, but covers broader deployment stacks rather than pure deep learning foundations.
Provides practical production machine learning tutorials, but covers broader deployment stacks rather than pure deep learning foundations.
SpecialistA vibrant open community for data science practitioners, though it operates as a network rather than structured courses.
SpecialistA vibrant open community for data science practitioners, though it operates as a network rather than structured courses.
Free / Open-sourcePublishes open-source datasets and research models, but focuses on raw AI research rather than structured educational tutorials.
Free / Open-sourcePublishes open-source datasets and research models, but focuses on raw AI research rather than structured educational tutorials.
SpecialistHosts hands-on AI hackathons and developer tutorials, but emphasizes rapid prototyping over deep academic machine learning.
SpecialistHosts hands-on AI hackathons and developer tutorials, but emphasizes rapid prototyping over deep academic machine learning.
Free / Open-sourceOffers free educational guides on prompt engineering, but focuses on LLM usage rather than training neural networks.
Free / Open-sourceOffers free educational guides on prompt engineering, but focuses on LLM usage rather than training neural networks.
Provides official structured learning resources for AI development, but centers on OpenAI's proprietary ecosystem rather than PyTorch.
Provides official structured learning resources for AI development, but centers on OpenAI's proprietary ecosystem rather than PyTorch.
Free / Open-sourceSupplies runnable open-source AI workflows, but serves as a code repository rather than a comprehensive teaching curriculum.
Free / Open-sourceSupplies runnable open-source AI workflows, but serves as a code repository rather than a comprehensive teaching curriculum.
Free / Open-sourceFree German-language online courses on the fundamentals of AI
Free / Open-sourceFree German-language online courses on the fundamentals of AI
SpecialistLearn AI by building, with a global community of makers
SpecialistLearn AI by building, with a global community of makers
