Prove
LiveProof-of-Work · Oct–Nov: every verified proof counts. 35 days leftAll outcomes
Skills

Learn Setup & Tooling (AI Engineering Phase 0)

4 weeks · 2 milestones

Phase 0 of AI Engineering from Scratch: 13 free lessons, then one project of your own that is run, evaluated and documented. Part of the Varsity Curriculum: AI Engineering.

Milestone map

Milestone map

2 milestones

Do the phase's lessons in public

1–1 weeks (about 10 hrs/week, est)

Work through the 13 lessons of Phase 0: Setup & Tooling from AI Engineering from Scratch (free) and keep the setup lessons' artifacts: your dev environment, git workflow, Python environments, Docker image, notebook and profiling runs in one public repo as you go. About 7 hours (est).

Proof required

Link your public repo with the setup lessons' artifacts: your dev environment, git workflow, Python environments, Docker image, notebook and profiling runs, and show your self-check (quizzes passed, notebooks run, tests passing where they exist).

What gets checked

  • The environment rebuilds from the README on a clean machine.
  • No API key or secret is in the repo or its history.
  • Each lesson's quiz is passed (shown).

Common mistakes

  • Copying the repo's solutions: verifiers read your history and ask about your code.
  • Skipping the self-check, then asking for review too early.

Powstik Guide

A public repo with the setup lessons' artifacts: your dev environment, git workflow, Python environments, Docker image, notebook and profiling runs.

Steps

  1. Make a public repo for this phase.
  2. Do one lesson at a time and commit after each.
  3. Self-check: Run each lesson's code; it must work on your machine as the lesson shows. Each lesson has a quiz (quiz.json, also on the course site): pass it.
  4. Write a short README: what is here and how to run it.
  5. Ask three people who know the topic to check it.

Template

README
Phase 0: Setup & Tooling (AI Engineering from Scratch)
What is here:
How to run it:
Self-check result:
What was hardest:

What gets sent back

  • One big upload with no history.
  • Self-check not shown.
  • Code that does not run from the README.

Resources

Foundationstart here

Depthgo deeper

What a verifier looks for

  • The environment rebuilds from the README on a clean machine.
  • No API key or secret is in the repo or its history.
  • Each lesson's quiz is passed (shown).
  • Ask about one choice in the code; the answer should be clear.

You'll sign in first, then come straight back here.

Make a reproducible AI dev setup

2–4 weeks (6–10 hrs/week)

Use what you learned. Make a starter repo for AI work with a pinned Python environment, a Dockerfile, a notebook that calls a model API with the key kept out of git, and one profiling run. It must run, be evaluated and be documented.

Proof required

Link a starter repo for AI work with a pinned Python environment, a Dockerfile, a notebook that calls a model API with the key kept out of git, and one profiling run, with a README that says how to run it and what the evaluation found.

What gets checked

  • It builds and runs from the README on someone else's machine.
  • The key is read from the environment, never committed.
  • The profiling output is shown and explained.

Common mistakes

  • A demo with no evaluation.
  • Numbers without the data or code that produced them.

Powstik Guide

A starter repo for AI work with a pinned Python environment, a Dockerfile, a notebook that calls a model API with the key kept out of git, and one profiling run.

Steps

  1. Write one line: what it does and for whom.
  2. Build the smallest version that works.
  3. Write the evaluation first, then improve against it.
  4. Write the README with the results.
  5. Ask three people to check it.

Template

README
What it does:
How to run it:
How it was evaluated:
Results:
Limits:

What gets sent back

  • Does not run from the README.
  • No evaluation.
  • Claims more than the evaluation shows.

Resources

Foundationstart here

What a verifier looks for

  • It builds and runs from the README on someone else's machine.
  • The key is read from the environment, never committed.
  • The profiling output is shown and explained.
  • Run it, or watch it run: it must work, be evaluated and be documented.
  • Check that the work is the person's own.

You'll sign in first, then come straight back here.