MLA-C01 · Question #29
MLA-C01 Question #29: Real Exam Question with Answer & Explanation
The correct answer is D: Create a Model Registry collection for each of the three categories. Move the existing model. SageMaker Model Registry Collections are a purpose-built organizational layer that sits above model groups, letting you group model groups into named collections without touching the underlying model packages or their existing structure - exactly what the question requires. Optio
Question
A company that has hundreds of data scientists is using Amazon SageMaker to create ML models. The models are in model groups in the SageMaker Model Registry. The data scientists are grouped into three categories: computer vision, natural language processing (NLP), and speech recognition. An ML engineer needs to implement a solution to organize the existing models into these groups to improve model discoverability at scale. The solution must not affect the integrity of the model artifacts and their existing groupings. Which solution will meet these requirements?
Options
- ACreate a custom tag for each of the three categories. Add the tags to the model packages in the
- BCreate a model group for each category. Move the existing models into these category model
- CUse SageMaker ML Lineage Tracking to automatically identify and tag which model groups
- DCreate a Model Registry collection for each of the three categories. Move the existing model
Explanation
SageMaker Model Registry Collections are a purpose-built organizational layer that sits above model groups, letting you group model groups into named collections without touching the underlying model packages or their existing structure - exactly what the question requires. Option A (tagging model packages) modifies metadata on individual model artifacts and doesn't provide a structural hierarchy, so it risks affecting existing package-level configurations and doesn't scale cleanly. Option B is disqualified outright by the constraint - moving models into new category-based model groups would destroy the existing groupings the data scientists already rely on. Option C is a red herring: ML Lineage Tracking records relationships between datasets, training jobs, and models for auditability, but it has no capability to categorize or tag model groups by team or domain.
Memory tip: Think of Collections as "folders for model groups" - just like moving a folder into a parent folder doesn't change the files inside, adding a model group to a Collection doesn't alter the models within it. The key phrase on the exam is "without affecting existing groupings" → that rules out any answer that moves or modifies model packages/groups, leaving Collections as the only non-destructive organizational option.
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