fast.ai

What fast.ai does

fast.ai is a San Francisco-based education nonprofit founded in 2016 by Jeremy Howard and Rachel Thomas to make deep learning accessible to programmers without requiring advanced mathematics, a PhD, or expensive compute. The organization delivers two free courses — Practical Deep Learning for Coders Part 1 (~13.5 hours across nine lessons) and Part 2 (30+ hours implementing Stable Diffusion from scratch) — alongside the 5-star rated companion book "Deep Learning for Coders with Fastai and PyTorch." Its core technology is the open-source fastai library, a high-level abstraction layer on PyTorch that the curriculum uses to teach computer vision, NLP, tabular analysis, collaborative filtering, and generative AI modalities.

The platform runs on a freemium community-led growth model with no paid acquisition: content is distributed freely via course.fast.ai, YouTube (over 6 million video views), GitHub, Google Colab, Kaggle Notebooks, and Paperspace Gradient. Monetization is intentionally minimal, consisting of optional Amazon book purchases, voluntary donations to the nonprofit, and ancillary goodwill that has historically produced alumni placements at Google Brain, OpenAI, Adobe, Amazon, Tesla, NeurIPS research publications, and competition wins such as the RA2-DREAM Challenge. The organization has formal collaborations with Kaggle (free GPU access), Hugging Face (Transformers and Diffusers libraries), Stability AI (Stable Diffusion curriculum), and the University of Queensland (course recording venue).

Strategically, fast.ai occupies a distinctive position as a high-credibility, non-commercial deep learning educator whose competitive advantage rests on Jeremy Howard's reputation, the alumni network effect, and the fastai library's technical standing. Growth is measured in student reach and curriculum depth rather than revenue, and the organization operates without venture backing, disclosed financials, or paid enterprise offerings. The implication for a PE/VC/M&A audience is that fast.ai is not a traditional investable target; it is best understood as a mission-driven nonprofit whose strategic value lies in its influence over the next generation of ML practitioners and its stewardship of the fastai open-source library.

Name

fast.ai

Legal name

fast.ai

Website

https://course.fast.ai

Company type

Private

Founded year

2016

Operating status

Operating

Headcount range

1–10 employees

Short description

fast.ai is a San Francisco education nonprofit that offers free, top-down deep learning courses and the open-source fastai PyTorch library to programmers worldwide, monetizing only via optional book sales and donations.

Ownership category

akta.pro rank

Product category

Deep Learning Education

NAICS

Educational Support Services (611710), Educational Support Services (61171), Exam Preparation and Tutoring (611691), Computer Training (611420)

SIC

Services-Educational Services (8200), Services-Prepackaged Software (7372)

akta.pro primary industry

AI/ML Learning Platforms for Students (EDAFANAE)

akta.pro secondary industries

AI-Powered Tutoring & Study Assistant Platforms (EDANAGAD), Education & Learning Personalization (HDAAAGAL)

Keywords

• Deep learning education
• Machine learning courses
• Open source AI library
• Online AI training
• Developer education

Headquarters

HQ city

San Francisco

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2C

Offering type

Services

Cost components

Personnel, Technology or R&D, Operations, Marketing or Sales

Revenue model

1. Educational content (free): The primary course and educational content are offered completely free of charge. This is a nonprofit educational organization that generates revenue through donations and complementary products rather than course fees.
2. Book sales: The companion book 'Deep Learning for Coders with Fastai and PyTorch' is available for purchase on Amazon as a paper book or Kindle ebook, providing supplementary revenue while the course remains free.
3. Donations: As an education nonprofit, fast.ai accepts donations to support operations and continue providing free education.

Pricing tiers

Go-to-market motion1 record

Distribution channels6 records

Marketing channels5 records

Core offering

fast.ai is an education nonprofit that delivers free, project-based online courses teaching practical deep learning, supported by the open-source fastai library (a PyTorch-based high-level deep learning library) and a 5-star-rated companion book. The flagship offering, "Practical Deep Learning for Coders," has two parts: Part 1 (~9 lessons, ~13.5 hours) covering computer vision, NLP, tabular analysis, collaborative filtering, and model deployment, and Part 2 (~30+ hours) implementing Stable Diffusion from scratch and deep learning foundations. An active online learner community reinforces the curriculum.

Product overview

fast.ai is an education-focused organization offering free online courses in deep learning. The core product portfolio consists of two parts of the "Practical Deep Learning for Coders" course: Part 1 (approximately 13.5 hours) covers foundational deep learning topics including computer vision, NLP, tabular analysis, and collaborative filtering using the fastai library built on PyTorch. Part 2 (over 30 hours) is an advanced course focused on implementing Stable Diffusion from scratch, covering diffusion models, transformers, and deep learning research paper reading. The curriculum is supported by a 5-star rated book ("Deep Learning for Coders with Fastai and PyTorch"), available both for purchase and free online. All resources are free, with the fastai library itself being open-source. The offering is complemented by an active online community forum.

Differentiator

Problem solved

Functional benefit

Products and services

• Practical Deep Learning for Coders (Part 1) Free online course of approximately 13.5 hours across 9 lessons (~90 minutes each) designed for people with coding experience; teaches building and training deep learning models for computer vision, NLP, tabular analysis, and collaborative filtering, plus deployment using PyTorch and the fastai library.
• Practical Deep Learning for Coders (Part 2: Deep Learning Foundations to Stable Diffusion) Free advanced course of over 30 hours implementing Stable Diffusion from scratch; covers diffusion models (DDPM/DDIM), transformers, attention mechanisms, U-Nets, autoencoders, backpropagation, optimization techniques, and reading deep learning research papers. Targets students who have completed Part 1 or have equivalent experience.
• fastai Library Open-source high-level deep learning library built on top of PyTorch, providing accessible abstractions for building and training neural networks; developed and led by Jeremy Howard, used throughout both course parts for rapid experimentation across computer vision, NLP, tabular, and collaborative-filtering tasks.
• Deep Learning for Coders with Fastai and PyTorch (Book) 5-star-rated companion book by Jeremy Howard and Sylvain Gugger that forms the basis of the course; available for purchase as paperback or Kindle ebook on Amazon, and freely readable online as interactive Jupyter notebooks via the fastbook GitHub repository. Contains 20 chapters covering deep learning fundamentals through advanced techniques.
• fast.ai Forums Online community forum at forums.fast.ai where students ask questions, share projects, collaborate on Kaggle competitions, and receive help; each lesson has a dedicated thread, and the community is a core part of the fast.ai learning experience.

Quantifiable outcome

• Students have become gold medal winners of international machine learning competitions
• +3 more outcomes

Named customers9 records

Segments4 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration6 records

AI capability12 records

Feature1 record

Partnerships

Four partnerships are on record, tiered core.

• University of QueenslandcoreStrategic or Co-development PartnerThe course was recorded at the University of Queensland, where co-founder Jeremy Howard served as a professor. The university provided the venue and academic context for the course development.
• KagglecoreTechnology or IntegrationKaggle provides free GPU access through their Notebooks platform for course students. Every lesson provides direct links to ready-to-run notebooks on Kaggle.
• Hugging FacecoreTechnology or IntegrationThe course extensively uses Hugging Face Transformers library and Diffusers library. Collaboration ensures rigorous coverage of the latest NLP and image generation techniques.
• Stability AIcoreStrategic or Co-development Partnerfast.ai worked closely with experts from Stability.ai to ensure rigorous coverage of Stable Diffusion and related techniques in Part 2 of the course.

Scale indicators4 records

Recent moves6 records

Expansion highlights5 records

Direct peers

• DeepLearning.AI: Founded by Andrew Ng, DeepLearning.AI offers free and paid online courses on deep learning and AI, serving the same global audience of programmers and practitioners looking to upskill in applied AI—making it the most direct comparable to fast.ai's free curriculum model.
• Kaggle Learn: Kaggle's free micro-courses cover introductory ML, deep learning, and computer vision with hands-on notebooks. Targets the same beginner-to-intermediate practitioner segment and shares platform-level integration with fast.ai's preferred notebook environment.

Broad incumbents

• Udacity: Originally founded on free university-style content (Sebastian Thrun's AI class that launched the MOOC era), now offers paid 'Nanodegree' programs in AI and deep learning. Comparable learning category but a more commercial, credential-oriented model.
• Coursera: Major MOOC platform hosting DeepLearning.AI, Andrew Ng's Machine Learning Specialization, and many university AI courses; directly competes for the same learner audience but at much larger scale, with paid certification and enterprise programs.
• DataCamp: Subscription-based platform offering interactive courses in Python, machine learning, and deep learning. Targets working professionals and data practitioners with a similar self-paced, code-first pedagogy to fast.ai.
• edX: University-affiliated MOOC platform hosting MIT, Harvard, and Berkeley AI courses including foundational deep learning content. Overlaps with fast.ai in serving self-learners seeking rigorous AI education, though with a more academic flavor.

Emerging players

• Hugging Face: Beyond its model hub, Hugging Face runs free educational content (NLP course, diffusion course) integrated with its Transformers/Diffusers libraries—an overlapping AI/ML learning pathway that competes with fast.ai Part 2's Stable Diffusion curriculum.
• StatQuest (Josh Starmer): Popular free video channel that demystifies statistics and machine learning concepts for practitioners. Shares fast.ai's accessible, theory-without-jargon pedagogical approach and targets self-taught developers entering ML.
• 3Blue1Brown: Grant Sanderson's video channel offering deep, visual explanations of neural networks and mathematics underpinning deep learning. Competes for the same 'free, top-quality conceptual understanding' audience that fast.ai targets, with strong YouTube distribution.
• Made With ML: Free, opinionated MLOps and applied ML curriculum focused on shipping production-grade models with PyTorch. Competes with fast.ai Part 2 on the 'code-to-production' dimension and serves a similar practitioner audience.

Market position

Strengths4 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• GitHubgithub.com/fastai
• YouTubeyoutube.com/playlist?list=PLfYUBJiXbdtSvpQjSnJJ_PmDQB_VyT5iU
• LinkedInlinkedin.com/school/fast-ai

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about fast.ai