Protocol
Formulate ML Problems and Audit Data
Audit one UCI dataset or a documented synthetic equivalent. Choose a task with an imperfect label and defend what the model can and cannot be used to decide.
30–50 active hours60–90 min sessionsIntermediate
Mastery contract
Core protocol · Standard 1.0 · Audit one UCI dataset or a documented synthetic equivalent. Choose a task with an imperfect label and defend what the model can and cannot be used to decide.
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Reasoning — not yet passed
The data contract states target availability, population, unit, decision cost and 5 plausible leakage routes.
Reliable implementation — not yet passed
Split checks enforce entity isolation and transformations fit only on training observations.
Reproducible experiment — not yet passed
The leaky-versus-defensible comparison uses the same model and reports the resulting bias without selecting the better-looking split.
Defense and handoff — not yet passed
Deliver a dataset card and defend one ambiguous labeling or exclusion decision with its impact on the target population.
All four criteria must pass. Activity completion does not satisfy them.
An independent reviewer reruns your work and varies something you did not rehearse: a fresh input, a different working directory, or a declared edge case.
Pilot decisions are provisional, not external credentials. For an appeal or sensitive artifact, contact your designated pilot operator with the submission ID. Export your assessment history.
What you will do
6 total
Define one target, prediction timestamp, sampling unit and decision cost; enumerate 5 leakage paths before fitting a model.
Implement a split-and-transform pipeline with training-only imputation/scaling, group isolation and persisted split IDs.
Compare a deliberately leaky random split with a defensible group or temporal split using a simple baseline; report why the apparent gain changes.
Debug duplicate entities across splits and a target-derived feature; write checks that reject both before training.
Write a 500–900 word technical report linking the reasoning, code, measurements, and limitations; include the project decision below.
Assess all 4 mastery criteria against saved artifacts, request an independent review, and repeat each failed criterion on a fresh example.
Essentials
A reading session alone never satisfies a mastery criterion.
Store source references, assumptions, and artifact paths beside every result.
Keep an untouched check case that differs from the worked example.
Record all attempts, including failures and results that contradict your prediction.
Use the stated comparison conditions; document every deviation before drawing a conclusion.
Protocol guardrails
Do
- +State the expected result before running the comparison.
- +Keep one minimal reproducible failing case when debugging.
- +Record environment versions and the exact command used.
- +Compare explanations with saved intermediate values.
- +Ask a reviewer to challenge the weakest assumption.
Don't
- ×Do not copy a worked solution and present it as an independent implementation.
- ×Do not tune against held-out evaluation outcomes.
- ×Do not report only the best seed or discard inconvenient runs.
- ×Do not equate elapsed hours or a completed run with a passed assessment.
- ×Do not conceal reduced-scale experiments behind claims about the original full-scale result.
Protocol authorship
Written by NuthinButta as instructional design. The teaching sources are the official references linked in each milestone; the exercises, workload and pass thresholds are ours, not their authors'.