# fastai/course-v3

The 3rd edition of course.fast.ai

Repository: https://github.com/fastai/course-v3
Canonical: https://ross.abutalabs.com/products/course-v3
Homepage: https://course.fast.ai/
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: data-science, fastai, deep-learning, pytorch, machine-learning, machine-learning-courses, mooc
Last push: 2024-05-21T09:10:37+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2883, "days_push": 834, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4911, forks 3470 (observed 2026-08-28T04:09:02.319906+00:00)

## What it is
The third edition of the fast.ai 'Practical Deep Learning for Coders' course, containing Jupyter notebooks and course materials. It is designed to be used with the fastai v1 library and is superseded by the fastbook repo for the latest course version.

## Use cases
- learn deep learning from scratch as a coder
- find course notebooks for practical deep learning lessons
- study computer vision and NLP model training examples
- follow a free MOOC on applying machine learning to real problems
- learn PyTorch and fastai through guided lessons

## When to choose
- you want the original v3 course notebooks that pair with fastai v1
- you are following the older recorded lessons of Practical Deep Learning for Coders
- you need free, hands-on deep learning course materials

## When to avoid
- you want the latest course content compatible with current fastai - use fastai/fastbook instead
- you need a maintained software library rather than course materials
- you are starting fresh and want up-to-date tooling

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, data-science
- domain: deep-learning, machine-learning, data-science, tutorials
- platform: python, cross-platform
- tags: mooc, jupyter-notebooks, pytorch, fastai, course-materials, education

## Member repositories
- fastai/course-v3 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:02.319906+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:18:04.276997+00:00, confidence not recorded.
  - readme: https://github.com/fastai/course-v3 (fetched 2026-08-28T04:09:02.319906+00:00, sha fba2e332d32e)
  - homepage: https://course.fast.ai/ (fetched 2026-08-29T09:00:03.965557+00:00, sha 24b10727ab7b)
- Data as of 2026-08-30T08:39:29.467469+00:00.