Learn Python with a friendly AI tutor — right on your own computer.

This is a ready-made workspace for learning Python. It gives you:

• A place to write and run Python — JupyterLab opens in your web browser; you write code in notebooks and run it with Shift+Enter.
• An AI tutor in the chat — ask @Tutor anything about Python, and it can create practice notebooks on any topic, just for you.
• AI that's free and private — by default the AI runs on your computer (via Ollama): no account, no cost, and nothing you type leaves your machine. (A cloud option exists too, if you want it.)
• The everyday Python libraries pre-installed — numpy, pandas, matplotlib, scipy — so examples from tutorials just work.

No programming experience needed — that's what you're here to get.

Three steps, all spelled out click-by-click in SETUP.md:

1. Install two free programs — Python and Ollama — then download an AI model (one command; it's a big download, so give it time).

2. Start the workspace:

   ./start.sh      # macOS / Linux (or double-click start.command on a Mac)
   .\start.cmd     # Windows (double-clicking start.cmd works too)

   The first run sets everything up (a few minutes); after that it starts in seconds. JupyterLab opens in your browser.

3. Open welcome.ipynb in JupyterLab and follow along — it checks your setup and gives you the tour.

If anything doesn't work, the fix is almost certainly in SETUP.md → When something goes wrong.

Want a structured path instead of wandering? lessons/ is a complete beginner course: eight notebooks, one ~45-minute session per week, from "what is Python?" to building your first small program. Lesson 1 is a light tour of the whole course, so you can decide after a single session whether it's for you.

Open a chat (the Chat card on the JupyterLab launcher) and talk to @Tutor:

• Ask anything: @Tutor what's the difference between a list and a tuple?
• Get a practice notebook: @Tutor new loops
• See the course lessons and your notebooks: @Tutor list

You

@Tutor new list comprehensions

Tutor

Scaffolding a practice notebook for list comprehensions …

• ✅ Created practice_list_comprehensions.ipynb (TOPIC pre-set, 1 cell updated).

Open it from the JupyterLab file browser and Run All.

Each practice notebook walks the same loop: explanation → exercises → your attempts → AI review. Run the AI cells again any time for a fresh set, or ask for harder ones.

Lessons and practice notebooks are two halves of one loop. The lessons/ course is the fixed path — the same eight hand-written notebooks for everyone, in order. Practice notebooks are the opposite: generated on demand, about whatever you need more reps on, as many as you like. A good rhythm: finish a lesson, then @Tutor new <something from that lesson> for extra practice before the next session. Lessons teach; practice notebooks make it stick.

There's also @Jupyternaut, the general assistant — great for "what does this error mean?" — and you can ask the AI from inside any notebook with the %%ai magic (the welcome notebook shows you how).

• docs/TEACHERS-GUIDE.md — classroom setup checklist, choosing models for your machines, running a class on a cloud model, customizing the Tutor for your course, and all the technical reference (memory tuning, model switching, how the launchers work, tests).
• docs/PERSONAS.md — build your own AI chat persona (the Tutor is a worked example you can copy).

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