Home / AWS Certified AI Practitioner (AIF-C01) / 4 Practice / AWS-AIF-362
Several teams use one model for different purposes.
Make scope and limits clear.
Choose two records.
Hint 1: Focus on the requirement Document purpose, limits, evidence, risks, ownership, and retirement criteria so a model can be governed after release.
Hint 2: Key terms Review model documentation and retirement criteria.
Model documentationA record of a model's purpose, data, evaluation, limits, risks, and version.
Intended useThe tasks and context for which a model has been designed and evaluated.
Prohibited useA context in which a model must not be used because of risk, contract, or performance limits.
Retirement criterionA condition used to decide that a model version should be taken out of service. × Incorrect Document purpose, prohibited use, data, evaluation, limits, risks, version, changes, approver, monitoring, and retirement conditions.
Detailed explanation A Incorrect Publish only the model name and average benchmark
Scope and limits remain unknown.
B Correct Record intended and prohibited uses, data, evaluation conditions, known limits, risks, and version
Users can judge applicability.
C Correct Update changes, approvers, monitoring, incident contacts, and retirement conditions
Operational ownership is traceable.
D Incorrect Reuse for a new purpose without updating documentation
Unexpected risks grow.
Check official documentation Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 4.2の文書化、説明責任、モデルガバナンスを確認する。
Official references Official documentation 1 Official documentation 2 What to confirm モデルをどこで使えるか、何が限界か、誰が管理するかを文書で示せる。
Key points Model documentation Limit Change history Notes Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認 Compare the definition with the AIF-C01 objective and the service documentation before applying it. Keep the concept separate from a particular answer choice or implementation step. Foundation review Model documentation A record of a model's purpose, data, evaluation, limits, risks, and version.
Intended use The tasks and context for which a model has been designed and evaluated.
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