AI-300 Practice Test 3 — 10 Questions

Question 1

A pipeline step fails because it cannot find a file in the datastore. What is the most likely cause?

Accepted Answer

Incorrect path definition in the component. The mount path or the relative path defined in the pipeline step component configuration is likely incorrect.

Answer

The workspace is too large

Answer

The compute cluster is off

Answer

The subscription is expired

Question 2

Which TWO of the following can be used to manage Azure ML assets like environments and models?

Accepted Answer

Azure CLI v2. The Azure ML Studio UI and the CLI v2 are both primary interfaces for asset management.

Answer

Azure Monitor

Answer

Azure Logic Apps

Answer

Power BI

Question 3

You need to audit all model access logs across your organization. What is the most effective approach?

Accepted Answer

Enable 'Diagnostic Settings' to send logs to a 'Log Analytics Workspace'.. Enabling diagnostic settings on the Azure AI Services resource to send logs to a Log Analytics workspace is the standard for organization-wide auditing.

Answer

Review individual request headers in the app logs.

Answer

Use 'Azure Advisor' to detect unauthorized access.

Answer

Download the 'Model Usage' report from the billing console.

Question 4

Which THREE of the following are components of an Azure AI Foundry project?

Accepted Answer

Prompt Flows.. Models, connections, and prompt flows are foundational components within the AI Foundry project environment.

Answer

Azure Key Vault (the resource itself).

Answer

Azure Subscriptions.

Question 5

What is the recommended approach for managing configuration settings for different environments (Dev, Test, Prod) in an AI application?

Accepted Answer

Use 'App Configuration' service to manage environment-specific variables.. Using environment variables or app configuration services is the standard way to inject configuration without hardcoding.

Answer

Deploy different model versions for each environment.

Answer

Create separate Azure subscriptions for every environment.

Answer

Hardcode values in the application code.

Question 6

You are deploying a model that requires specific GPUs. How do you ensure you get the right infrastructure?

Accepted Answer

Choose the correct SKU during model deployment.. Selecting the appropriate SKU (e.g., standard vs. GPU-optimized) during the deployment process ensures you get the required infrastructure.

Answer

Add the model to a resource group.

Answer

Update the OS of the node.

Answer

Request a quota increase for CPU.

Question 7

You are deploying a large model. During the deployment, you encounter a 'Resource Not Available' error. What is the most likely cause?

Accepted Answer

The region does not have capacity for the requested model SKU.. This error usually indicates that the region lacks sufficient capacity for the specific SKU requested.

Answer

The API key is invalid.

Answer

The project name is too long.

Answer

The subscription is not registered for the service.

Question 8

You are deploying a custom model in a container. To ensure the model infrastructure is highly available, what is the best practice?

Accepted Answer

Deploy to 'Azure Kubernetes Service' with 'Availability Zones' enabled.. Deploying across multiple Availability Zones ensures that the infrastructure remains operational even if a specific datacenter fails.

Answer

Disable the 'Load Balancer' to save costs.

Answer

Use a 'Standard' tier App Service plan.

Answer

Deploy the container on a single large VM.

Question 9

Which THREE metrics are critical for monitoring the health of a GenAI deployment?

Accepted Answer

Request Latency.. Latency, throughput (tokens per second), and error rates are the standard health metrics for AI deployments.

Answer

User email addresses.

Answer

CPU Usage of the host node.

Question 10

In an LLM evaluation workflow, what does the 'Coherence' metric measure?

Accepted Answer

The logical flow and structure of the output. Coherence measures how well a model-generated answer makes sense and flows logically as a human-like response.

Answer

The length of the response

Answer

The presence of offensive language

Answer

The factual accuracy of the answer