Practice Questions
Question 1
You train multiple machine learning models using different algorithms and want to store them in a central location with version tracking. Which Azure Machine Learning capability should you use?
A. Azure Kubernetes Service
B. Model registration
C. Batch endpoints
D. Automated machine learning
Correct Answer: B
Explanation:
Model registration stores trained models in Azure Machine Learning, enabling centralized management, versioning, and reuse.
Question 2
Why is model versioning important in Azure Machine Learning?
A. To reduce compute costs
B. To allow rollback to previous model versions
C. To encrypt model files
D. To improve model accuracy automatically
Correct Answer: B
Explanation:
Model versioning allows teams to track changes over time and revert to earlier versions if newer models perform poorly.
Question 3
Which deployment option should you use when predictions must be returned immediately to a web application?
A. Batch endpoint
B. Training pipeline
C. Real-time endpoint
D. Experiment run
Correct Answer: C
Explanation:
Real-time endpoints provide low-latency predictions through REST APIs, making them suitable for applications that need immediate responses.
Question 4
A data science team wants to score millions of records overnight without requiring instant responses. Which deployment approach is most appropriate?
A. Real-time endpoint
B. Batch endpoint
C. Azure Functions
D. Model registration
Correct Answer: B
Explanation:
Batch endpoints are designed for large-scale, offline predictions and do not require low-latency responses.
Question 5
Which Azure Machine Learning feature tracks metrics, parameters, and outputs from training runs?
A. Model deployment
B. Experiment tracking
C. Model endpoint
D. Azure Blob Storage
Correct Answer: B
Explanation:
Experiment tracking captures training details such as metrics and parameters, enabling comparison and reproducibility.
Question 6
After training a model, what is the primary purpose of registering it in Azure Machine Learning?
A. To retrain the model automatically
B. To expose the model as an API
C. To store and manage the model for future use
D. To encrypt the dataset
Correct Answer: C
Explanation:
Registering a model allows it to be stored, versioned, and managed, making it available for deployment and reuse.
Question 7
Which Azure Machine Learning capability simplifies scaling and infrastructure management when deploying models?
A. Model versioning
B. Containerized deployment
C. Experiment tracking
D. Data labeling
Correct Answer: B
Explanation:
Azure Machine Learning packages models into containers, simplifying deployment, scaling, and infrastructure management.
Question 8
What is a key difference between real-time endpoints and batch endpoints?
A. Real-time endpoints do not require models
B. Batch endpoints are used only for training
C. Real-time endpoints provide immediate predictions
D. Batch endpoints use more accurate models
Correct Answer: C
Explanation:
Real-time endpoints return predictions immediately, while batch endpoints process large datasets asynchronously.
Question 9
Which task is part of model management rather than model deployment?
A. Exposing a REST API
B. Scaling compute resources
C. Registering and versioning models
D. Handling prediction requests
Correct Answer: C
Explanation:
Registering and versioning models are model management tasks. Deployment focuses on making models available for predictions.
Question 10
Which statement best describes Azure Machine Learning’s role in model deployment?
A. It requires manual server configuration
B. It automates model training only
C. It simplifies deploying models to scalable endpoints
D. It replaces Azure Kubernetes Service
Correct Answer: C
Explanation:
Azure Machine Learning abstracts infrastructure complexity, making it easier to deploy models as scalable endpoints.
Final Exam Tips ✅
- Model registration = storage + versioning
- Real-time endpoint = immediate predictions
- Batch endpoint = large-scale, offline predictions
- AI-900 tests concepts, not implementation details
Go to the AI-900 Exam Prep Hub main page.
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