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Machine Learning Foundations / Module 5

Module 5 check

Module 05 Assessment: Generalisation and Leakage Check

Assessment ID: ML-M05-QA01 Estimated active time: 35-50 minutes Status: Draft

Part A: Concept checks

Answer in one or two sentences.

  1. What score did a model achieve using every column, including post-outcome ones?
  2. Which single column was doing that work, and how did you identify it?
  3. What is the score once the leaking columns are removed?
  4. Explain the gap between those two numbers in one sentence.
  5. From your learning curve, is more data or a better model the constraint?

Part B: Applied task

Use the supplied synthetic dataset to complete the module activity: Compare a leaky experiment with a repaired one and explain why the score changed.

Part C: Explanation

Explain the leak, the honest score, and what your learning curve says about where to spend effort next.

Rubric

LevelEvidence
PassCompletes the activity, explains the output in plain English, compares or limits the result properly, and avoids overclaiming.
ReviseCompletes most of the task but misses one important comparison, limitation, or data-safety boundary.
Not yetTreats synthetic results as real-world proof, omits the required evidence, or ignores the module safety rule.

Safety rule

Do not use real personal, confidential, employer, client, health, financial, authentication, or sensitive data.