easyMultiple Choice
AIF-C01 Practice Question: Wants to document key information about their…
An organization wants to document key information about their machine learning model, including intended use, performance metrics, training data, and ethical considerations. Which tool or practice should they adopt?
⚠ Common exam trap
The trap is confusing model cards (model-level documentation) with data sheets (dataset-level documentation) or with registries that store artifacts rather than describe them.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Model cards
Model cards are structured documents that describe a model's intended use, performance across relevant subgroups, training data provenance, and ethical considerations such as bias and limitations. They were popularized by Google and are now a standard responsible-AI artifact. This matches the question's requirement to document intended use, metrics, training data, and ethics in one place.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SageMaker Model Registry
Why it's wrong here
SageMaker Model Registry catalogues model versions, approval status and deployment lineage, but does not capture intended use, ethical considerations or training-data detail. It is tempting because it centralises model governance artefacts, and would be correct when the need is version tracking and approval workflow rather than narrative documentation.
- ✗
Data sheets
Why it's wrong here
Data sheets document datasets, covering provenance, composition and collection methods, not a model's intended use, performance metrics or ethical considerations. They are tempting because dataset transparency underpins responsible AI, and they would be the right artefact when the requirement centres on describing the training data itself.
- ✓
Model cards
Why this is correct
Model cards are short structured documents recording a model's intended use, performance metrics, training data and ethical considerations. They satisfy the documentation requirement directly, giving stakeholders a standardised reference for each model's purpose, limitations and fairness characteristics.
- ✗
AWS CloudTrail logs
Why it's wrong here
CloudTrail records API activity and account events, not model documentation such as intended use, metrics or ethical considerations. It is tempting because it provides an audit trail of who trained or deployed a model, which supports governance evidence, but it captures actions rather than the model's documented characteristics.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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