Agent skill · research science · aradotso
ai-engineering-from-scratch
ai-engineering-from-scratch — an agent skill for coding agents.
Why this skill is useful
Provides a comprehensive curriculum with 230+ hands-on lessons and reusable artifacts for AI engineering, significantly enhancing the AI's ability to learn and implement complex concepts.
What it needs
Requires julia, node, python, rust installed locally. Requires anthropic, google, huggingface, openai account access. About 9k tokens when loaded. Last updated 2026-07-09. 70 stars on the source repository.
What this skill does
ai-engineering-from-scratch/ ├── phases/ │ ├── 00-setup-and-tooling/ │ │ ├── 01-dev-environment/ │ │ ├── 02-git-and-collaboration/ │ │ └── ... │ ├── 01-math-foundations/ │ ├── 02-ml-fundamentals/ │ ├── 03-deep-learning-core/ │ ├── 04-computer-vision/ │ ├── 05-nlp-foundations-to-advanced/ │ ├── 06-speech-and-audio/ │ └── ... (phases 07–19) ├── assets/ ├── glossary/ │ └── terms.md ├── ROADMAP.md ├── CONTRIBUTING.md └── README.md phases/NN-phase-name/NN-lesson-name/ ├── README.md # lesson explanation and goals ├── solution.py # reference implementation ├── notebook.ipynb # interactive walkthrough ├── requirements.txt # lesson-specific dependencies └── tests/ # validation tests bash Python 3.10+ python --version Node.js 18+ (for TypeScript lessons) node --version Rust (for Rust lessons) rustup --version Julia (for math lessons) julia --version bash git clone https://github.com/rohitg00/ai-engineering-from-scratch.git cd ai-engineering-from-scratch bash Create a base environment python -m venv .venv source .venv/bin/activate # Windows: .venv\Scripts\activate Or use conda conda create -n ai-eng python=3.11 conda activate ai-eng Install base dependencies pip install -r requirements.txt # if present at root Install lesson-specific deps pip install -r phases/01-math-foundations/01-linear-algebra-intuition/requirements.txt bash pip install numpy scipy matplotlib pandas scikit-learn pip install torch torchvision torchaudio # deep learning pip install transformers datasets tokenizers # HuggingFace pip install openai anthropic # LLM APIs pip install jupyter notebook ipykernel # notebooks pip install pytest black ruff # dev tools bash export OPENAIAPIKEY="your-key-here" export ANTHROPICAPIKEY="your-key-here" export HUGGINGFACETOKEN="your-token-here" export GOOGLEAPIKEY="your-key-here" python from dotenv import loaddotenv import os loaddotenv() apikey = os.getenv("OPENAIAPIKEY") bash Start Jupyter for a specific phase cd phases/01-math-foundations/01-linear-algebra-intuition/ jupy …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/ai-engineering-from-scratch