Available draft · two ninety-minute units · construction edition
Attempt the student work before consulting the solutions. Untouched exercises intentionally report NEEDS_WORK.
| Session | Notebook | Matching text | Purpose |
|---|---|---|---|
| A · 90 minutes | A: controlled improvement | Markdown | Construct, connect and explain |
| B · 90 minutes | B: winner's curse and preferences | Markdown | Derive, check against simulation and transfer |
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Each notebook includes its own setup, first-principles introductions and supplied teaching runtime. Open either notebook in Google Colab with its badge, or use a local Python 3.12+ Jupyter kernel; Unit A also needs Pydantic 2, and Unit B only the standard library. No repository checkout, previous notebook kernel or live account is needed. Unit A closes with an extension that puts a language model behind the chapter's own tools: a recorded transcript runs everywhere, and an OpenAI key in Colab's Secrets pane switches the same loop to a live gpt-5.1 run. Unit B predicts the winner's curse from first principles, checks it against simulation, and builds the Bradley–Terry gradient behind reward models. Unit B can use an explicitly selected successful Unit A handoff; an invalid selected file refuses rather than substituting an answer.
Ninety minutes is the planned work allowance per unit, excluding installation. Actual completion time and understanding require classroom observation.
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