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Machine Learning Foundations / Module 2

Module 2 activity

Activity: Create a Data Audit

Activity ID: ML-M02-A01 Estimated active time: 40-55 minutes

Goal

Create a data audit for the supplied synthetic learner-progress dataset.

Inputs

  • data/learner_progress_audit_v1.csv
  • data/data-dictionary.md
  • data/schema.json
  • data/provenance.md

Instructions

  1. Open the dataset and dictionary.
  2. Identify the unit of analysis.
  3. Identify the target.
  4. List valid day-3 feature candidates.
  5. List columns that must be excluded from features.
  6. Count missing values.
  7. Count target values.
  8. Flag proxy and measurement risks.
  9. Write a continue, revise, or stop decision.

Submission table

FieldYour answer
Unit of analysis
Prediction time
Target
Valid feature candidates
Excluded columns
Missing-value notes
Target balance
Proxy-risk columns
Measurement concerns
Coverage concerns
Continue, revise, or stop

Quality checklist

  • [ ] Target is not listed as a feature.
  • [ ] Future-information columns are excluded.
  • [ ] Missing values are counted and explained.
  • [ ] Proxy-risk columns are named.
  • [ ] Decision is limited to a learning exercise.

Safety note

Use only the supplied synthetic data. Do not add or upload real learner data.