- A
A public marketplace where organisations can buy pre-trained models from third parties
Why wrong: Model marketplaces are commercial platforms — the ML model registry is an internal version-control store for your organisation's models.
- B
A centralised versioned store for tracking and managing trained models and their lineage
The model registry stores all model versions with metadata and lineage — enabling comparison, rollback, and controlled deployment.
- C
A database of domain-specific vocabularies used for NLP model training
Why wrong: Vocabulary databases are NLP training resources — the model registry manages trained model artefacts and their version history.
- D
A compliance register documenting AI models used by an organisation for audit purposes
Why wrong: Audit compliance registers are governance documents — the model registry is a technical system for ML model versioning and deployment.
AI-900 Practice Question: Describe fundamental principles of machine learning on Azure
This AI-900 practice question tests your understanding of describe fundamental principles of machine learning on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
What is 'model registry' in Azure Machine Learning?
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
A centralised versioned store for tracking and managing trained models and their lineage
The model registry in Azure Machine Learning is a centralized, versioned store that tracks trained models along with their metadata, lineage, and lifecycle. It enables data scientists to register, version, and manage models, ensuring reproducibility and governance across the ML lifecycle.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A public marketplace where organisations can buy pre-trained models from third parties
Why it's wrong here
Model marketplaces are commercial platforms — the ML model registry is an internal version-control store for your organisation's models.
- ✓
A centralised versioned store for tracking and managing trained models and their lineage
Why this is correct
The model registry stores all model versions with metadata and lineage — enabling comparison, rollback, and controlled deployment.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
A database of domain-specific vocabularies used for NLP model training
Why it's wrong here
Vocabulary databases are NLP training resources — the model registry manages trained model artefacts and their version history.
- ✗
A compliance register documenting AI models used by an organisation for audit purposes
Why it's wrong here
Audit compliance registers are governance documents — the model registry is a technical system for ML model versioning and deployment.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse the model registry with a marketplace or compliance tool, but the exam specifically tests the registry's role as a versioned repository for managing model artifacts and their lineage.
Detailed technical explanation
How to think about this question
Under the hood, the model registry stores each registered model as an asset with a unique ID, version number, and associated run ID from training. It captures lineage by linking to the training script, dataset, and environment used, enabling full reproducibility. In a real-world scenario, a team can promote a model from staging to production by updating its stage tag (e.g., 'Production') in the registry, while keeping all previous versions for rollback or audit.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe fundamental principles of machine learning on Azure — This question tests Describe fundamental principles of machine learning on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: A centralised versioned store for tracking and managing trained models and their lineage — The model registry in Azure Machine Learning is a centralized, versioned store that tracks trained models along with their metadata, lineage, and lifecycle. It enables data scientists to register, version, and manage models, ensuring reproducibility and governance across the ML lifecycle.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
This AI-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-900 exam.
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