Written explainers. No setup, no code to run — read them in the browser.
| Document | Length | What it covers |
|---|---|---|
| Get Started with AI | Short | What AI is, why it resists definition, and the four things AI systems actually do |
| Generative AI: An Overview | Medium | Why ChatGPT changed the conversation; summarisation, translation, image and speech generation; what "prediction, not thinking" means |
| Generative AI In Depth | Medium | The layers of the AI stack, what's driving progress, and the honest limitations — hallucination, privacy, plagiarism, energy cost |
| AI Syllabus | Reference | The full topic checklist, from linear algebra to research methodology |
| Git and GitHub | Short | Version control basics — repositories, commits, branches, pull requests |
Completely new to AI? Get Started with AI → Generative AI: An Overview → Generative AI In Depth. About an hour end to end, and you'll be able to follow most AI conversations afterwards.
About to contribute? Git and GitHub first, then CONTRIBUTING.md.
Planning a study path? AI Syllabus is the checklist; the roadmap is the schedule. Use them together — the syllabus tells you what exists, the roadmap tells you what order to meet it in.
Prose that teaches a concept belongs here. Code that demonstrates one belongs in
notebooks/; a link to someone else's writing belongs in the
main README.
- Lowercase, hyphen-separated filename
- Open with an H1 title and a one-line summary of what the reader will know afterwards
- Write for someone who has never seen the topic before
- Link the sources you learned it from at the end
- Add a row to the table above and to the main README
See CONTRIBUTING.md.