rohitg00/ai-engineering-from-scratch

This page introduces an external open-source repository. It is not an HDATF product.

What it does

An open-source curriculum of 523 lessons that teaches AI engineering from math foundations to agents, using Python, TypeScript, Rust and Julia. Each lesson ships a reusable artifact such as a prompt, skill, agent or MCP server.

How it helps ATF

Mainly learning material rather than a product component. Its lessons on agents, skills and MCP servers could serve as background reading for engineers working on Harness.

License

MIT Permissive. Commercial use and changes are allowed if the copyright notice is kept.

More in this category

• byoungd/up
  A continually updated guide to lifelong learning in the AI era, covering English learning, learning with AI, real projects, startup failure and personal recovery. It is offered in Chinese and English as EPUB and PDF.
• rmyndharis/OpenWA
  A self-hosted WhatsApp API gateway with a React dashboard for sessions, webhooks and API keys. It runs several WhatsApp sessions on one instance, and the database, storage and cache backends are chosen through config.
• DigitalPlatDev/FreeDomain
  Public information and learning resources for DigitalPlat FreeDomain, a free domain registration service whose domains can use custom nameservers. It includes a tutorial and a guide covering DNS, websites, email and operations.
• trimstray/the-book-of-secret-knowledge
  The Book of Secret Knowledge is a curated collection of lists, manuals, cheatsheets, blogs, one-liners and CLI and web tools. It is aimed mainly at system and network administrators, DevOps engineers, pentesters and security researchers.
• unicity-sphere/sphere-sdk
  A TypeScript SDK for Unicity wallet operations, aimed at autonomous economic agents. It covers key management, token payments and payment requests, a signed intent board with semantic search, Nostr-based messaging and group chat, and dApp connections.

Only repositories in the ranked Trendshift lists are included, and the lists are used only to find candidates. We do not copy their ranks. Descriptions, licenses and star counts come from each GitHub repository. The notes are our own reading. We have not tested these projects, and a place on a trending list does not prove quality.