AI-300 Practice Test 12 — 15 Questions

Question 1

Which THREE settings are part of the 'InferenceConfig' object in Azure ML?

Accepted Answer

Source directory.. Entry script, environment, and property settings are part of the inference config.

Answer

Target storage account URL.

Answer

Compute instance size.

Question 2

You want to automate the deployment of a model using GitHub Actions. Which file format is standard for defining the Azure ML CLI v2 deployment configuration?

Accepted Answer

YAML. Azure ML CLI v2 uses YAML files to define configurations for jobs, endpoints, and deployments.

Answer

JSON

Answer

XML

Answer

Bicep

Question 3

You are managing a multi-workspace environment. You need to restrict the ability to create new compute clusters to only specific users. Where should you apply this control?

Accepted Answer

Azure RBAC on the Workspace. RBAC (Role-Based Access Control) at the workspace level determines which users can interact with compute resources.

Answer

Network Security Group

Answer

Azure Storage Access Policies

Answer

Azure ML Datastore configuration

Question 4

What is the primary benefit of using Azure ML compute clusters instead of compute instances for training?

Accepted Answer

Support for multiple nodes. Compute clusters are designed for distributed, scalable training across multiple nodes.

Answer

Clusters have more RAM per node

Answer

Instances are deprecated

Answer

Cost is always lower

Question 5

Which TWO of the following are required to secure an Azure ML workspace using a Private Link?

Accepted Answer

A Virtual Network (VNet). A Private Endpoint and a specific VNet configuration are core to the Private Link setup.

Answer

Public IP address

Answer

Data Factory instance

Answer

Azure Active Directory B2C

Question 6

You have an automated deployment pipeline. You want to run an integration test on the model after deployment. Which tool is best suited for this?

Accepted Answer

Azure DevOps pipelines.. 'Azure DevOps' (or GitHub Actions) is the industry-standard tool for orchestrating post-deployment testing as part of a CI/CD pipeline.

Answer

A manual 'Endpoint' health check.

Answer

The training script.

Answer

Azure Machine Learning Studio 'Tests' tab.

Question 7

You need to prevent data egress from your Azure ML environment. What configuration is required?

Accepted Answer

Managed VNet and egress locks. A workspace with no public IP and a managed virtual network with egress controls prevents unauthorized data movement.

Answer

Enable public access

Answer

Use a public load balancer

Answer

Create a new resource group

Question 8

You are configuring a 'Managed Online Endpoint' for production. You want to ensure high availability. What should you configure?

Accepted Answer

Set the 'instance_count' to at least 2.. To ensure high availability, you should configure the 'instance_count' to be greater than 1, spanning multiple availability zones if supported.

Answer

Use 'LowPriority' compute.

Answer

Set the 'instance_count' to 1.

Answer

Enable 'Auto-scaling' only.

Question 9

Which TWO actions can you perform in the Azure Machine Learning studio?

Accepted Answer

View run history.. Experiment management and data asset management are core UI functions.

Answer

Modify global azure subscriptions.

Answer

Manage office 365 users.

Answer

Configure networking in the tenant.

Question 10

You are deploying a model as a real-time endpoint. You want to ensure the deployment can handle sudden spikes in traffic. Which scaling configuration should you enable?

Accepted Answer

Auto-scaling. Auto-scaling allows the endpoint to dynamically adjust node count based on CPU/Memory usage.

Answer

Static node count

Answer

Batch deployment

Answer

Pre-warmed instances

Answer

None of the above

Question 11

Which TWO languages are natively supported for the Azure ML SDK?

Accepted Answer

R.. Python and R are the primary languages with official SDK support.

Answer

Pascal.

Answer

Basic.

Answer

Fortran.

Question 12

You need to ensure that a training script running on Azure ML has access to secrets (like API keys) without hardcoding them in the script. What should you use?

Accepted Answer

Azure Key Vault. Azure Key Vault is integrated with Azure ML to securely manage and inject secrets into training jobs.

Answer

Environment variables in the Dockerfile

Answer

Local configuration files

Answer

Hardcoding in the script

Question 13

You need to orchestrate a series of ML steps (Data prep, Training, Evaluation). Which Azure ML feature is specifically designed for this?

Accepted Answer

Azure ML Pipelines. Azure ML Pipelines allow you to string together components into a workflow.

Answer

Notebooks

Answer

Batch endpoints

Answer

AutoML

Question 14

What is the primary function of an Azure ML 'Datastore'?

Accepted Answer

Connection to storage services. Datastores are abstractions to securely connect to underlying data storage services like Blob storage or Data Lake.

Answer

Experiment tracking

Answer

Model registry

Answer

Compute resource management

Question 15

In Azure ML, what is a 'Component'?

Accepted Answer

A reusable pipeline step. A component is a reusable, versioned building block for an ML pipeline.

Answer

A storage account

Answer

A user role

Answer

A physical server