Data science
Covered in practiceStatistics, modelling, evaluation, and experiments.
What to look for
- Define the target and unit of evaluation first.
EXAM KNOWLEDGE MAP
Break the scope into locatable knowledge areas, then return each error to its concept and decision steps.
Original items train the published ability scope. Practice scores are not official scores, and official samples are not copied.
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QUICK REFERENCE
Keep the exam's scattered terms on one compact index. Scan the names first, then open only the items whose meaning or decision point needs a check.
SYLLABUS AT A GLANCE
Statistics, modelling, evaluation, and experiments.
Collection, quality, SQL, pipelines, and security.
Problem definition, KPIs, communication, and ethics.
Generative-AI use, risks, ethics, and organizational controls.
OFFICIAL REFERENCE