ScaDaMaLe -- Scalable Data Science and Distributed Machine Learning

Open course materials by VakeWorks. Each cohort/year is a directory: 2026/ (this run), then 2027/, and a rolling latest/.

• The book (PDF): https://vake.works/courses/ScaDaMaLe/ScaDaMaLe-Book-2026.pdf
• The 2026 labs: 2026/labs/

Labs are Apache-2.0; the book text is CC-BY-SA-4.0. See LICENSE.

Getting started (new to Git? start here)

You need three tools: git, ssh, and docker. The book's Foundations chapters "The Linux shell" and "Git, SSH and the sovereign centre" teach these from scratch -- read them first if any of this is new (book PDF, Foundations part).

1. Install git.

• Ubuntu/Debian: sudo apt update && sudo apt install -y git
• macOS: xcode-select --install (or brew install git)
• Windows: install Git for Windows, then use Git Bash
• Verify: git --version

2. Clone this repository.

git clone https://git.vake.works/vakeworks/scadamale.git
cd scadamale/2026/labs

(Mirrors, if the primary is busy: codeberg.org, github.com, gitlab.com -- all vakeworks/scadamale.)

3. Run a lab. Each lab is self-contained; cd into it and follow its README.md:

cd lab0-toolchain
bash run-lab.sh

Lab 0 checks your toolchain (git + ssh + docker) and runs the proof-checker on a one-line theorem -- do it first. Then lab1-alpha-beta and lab2-sample-sort-spark. Every lab writes a timestamped receipt you keep as your submission evidence (see 2026/labs/README.md).