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Project phase 1
Plan the work
State the goal, audience or user, and the evidence a strong result needs. Explain how Exploratory data analysis changes your plan.
Machine Learning with Python · Lesson 1 project
Produce a dataset-readiness report
A variable inventory, quality audit, suitable chart plan, two safe questions, and two claims the sample cannot support.
Lesson project · EDA notebook
Produce a dataset-readiness report
A variable inventory, quality audit, suitable chart plan, two safe questions, and two claims the sample cannot support.
0%0 of 3 checks
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Project phase 2
Create the deliverable
Inspect a small dataset before predicting anything. Classify each variable, identify missing or implausible values, draw one suitable chart, and write two questions the sample cannot answer safely.
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Project phase 3
Prove and improve
Use Sample bias and Variable type to check the result. Record one piece of evidence, one correction, and one improvement you would make next.
Close the loop
Explain what changed.
After the checks pass, name one decision, one failure you corrected, and one improvement you would make next. That explanation is part of the project.