fast.ai
course.fast.ai
Spec sheet
- Integrations
- The fastai documentation includes guides for using it with plain PyTorch, Ignite, Lightning, and Catalyst.Read 11 Oct 2026 · docs.fast.ai
- Support
- The course directs learners who need help to the fast.ai online community forum.Read 11 Oct 2026 · course.fast.ai
- Founded
- 2016Read 28 Sep 2026 · course.fast.ai
- Course format
- Part 1 has nine lessons of around 90 minutes each, and the course page also links a Part 2 video course described as over 30 hours.Read 11 Oct 2026 · course.fast.ai
- Course platforms
- The course recommends Kaggle Notebooks and Paperspace Gradient, and says some parts are done on the learner’s own laptop.Read 11 Oct 2026 · course.fast.ai
- Course software
- The course uses PyTorch, fastai, Hugging Face Transformers, and Gradio.Read 11 Oct 2026 · course.fast.ai
- Course topics
- Practical Deep Learning for Coders covers computer vision, natural language processing, tabular analysis, collaborative filtering, random forests, regression, and model deployment.Read 11 Oct 2026 · course.fast.ai
- Library features
- The library documentation lists a GPU-optimized computer vision library, an optimizer, a callback system, and a data block API among its components.Read 11 Oct 2026 · docs.fast.ai
- Library installation
- The documentation says fastai can be used without installation in Google Colab or installed locally with `pip install fastai`.Read 11 Oct 2026 · docs.fast.ai
- Library purpose
- The fastai library provides high-level components for practical deep learning and low-level components researchers can combine to build new approaches.Read 11 Oct 2026 · docs.fast.ai
- Organization
- The about page describes fast.ai as a research institute dedicated to making deep learning more accessible and identifies Jeremy Howard and Rachel Thomas as co-founders.Read 11 Oct 2026 · fast.ai
- Prerequisites
- The course says learners should know how to code, preferably in Python, and have followed a high school math course.Read 11 Oct 2026 · course.fast.ai
- Security and compliance
- The opened official pages do not state security certifications or compliance claims.Read 11 Oct 2026 · fast.ai
- What it is
- fast.ai offers free courses, a software library, research, and a community to make deep learning easier to use and more accessible.Read 11 Oct 2026 · fast.ai
- Windows support
- The documentation says Jupyter on Windows resets DataLoader `num_workers` to 0 to avoid hangs, which can make some computer vision tasks slower than on Linux.Read 11 Oct 2026 · docs.fast.ai
Plans and prices
Practical Deep Learning for Coders Free Free online course; coding experience is the only prerequisite stated Read 11 Oct 2026 · course.fast.ai
Where Specifiction places it
- MOOC Platforms#26 of 678.1