AI-300 Practice Test 2 — 25 Questions

Question 1

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 2

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 3

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 4

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 5

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

Question 6

You need to ensure that your LLM responses are filtered for harmful content. Which infrastructure component provides this capability?

Accepted Answer

Azure AI Content Safety. Azure AI Content Safety is the integrated service used within AI Foundry to monitor and filter model outputs.

Answer

Azure Monitor

Answer

Azure Key Vault

Answer

Azure Bastion

Question 7

You are automating the deployment of your AI project. What is the recommended tool to manage infrastructure-as-code (IaC) for Azure AI Foundry?

Accepted Answer

Azure Bicep. Bicep is the native, recommended IaC tool for Azure, providing deep integration for AI Foundry resources.

Answer

Azure DevOps pipelines

Answer

Azure CLI alone

Answer

Python script with Azure SDK

Question 8

You are onboarding a team to Azure AI Foundry. You need to assign the minimum permissions for a developer to deploy and test a model. Which role should you assign?

Accepted Answer

Azure AI Developer. The 'Azure AI Developer' role provides sufficient permissions to manage resources and perform model deployments within the project.

Answer

Owner

Answer

Reader

Answer

Contributor

Question 9

You notice your model deployment status is 'Succeeded' but inference requests are failing. Where should you first check for connectivity issues?

Accepted Answer

The 'Endpoints' tab in Azure AI Foundry. The 'Endpoints' view in the AI Foundry project shows the connectivity status and endpoint URLs for the model.

Answer

The 'Keys' tab in the Azure Portal

Answer

Azure Subscription usage reports

Answer

Azure Storage Account logs

Question 10

Which TWO of the following are valid ways to authenticate to an Azure AI Foundry project?

Accepted Answer

API Keys.. Entra ID (RBAC) and API Keys are the two primary methods for securing access to AI resources.

Answer

Hardcoded usernames in the code.

Answer

Local file-based passwords.

Answer

Public IP allow-listing only.

Question 11

Which TWO of the following are benefits of using Prompt Flow for orchestration?

Accepted Answer

Integrated testing and evaluation.. Prompt Flow offers a visual interface for complex flows and integrated evaluation, which simplifies orchestration.

Answer

Removal of the need for an LLM.

Answer

No need for authentication.

Answer

Automatic hardware management.

Question 12

Which TWO metrics are most useful for evaluating the 'User Experience' in a conversational agent?

Accepted Answer

Relevance. Latency and the quality of the answer (Relevance) are the primary drivers of user satisfaction.

Answer

Disk I/O speed

Answer

Model training loss

Answer

GPU voltage

Question 13

You are planning a production GenAI deployment. Which THREE of the following are necessary infrastructure considerations?

Accepted Answer

Implementing Private Link for network isolation.. Security, scalability, and monitoring are the three pillars of a production-ready AI infrastructure.

Answer

Using the cheapest SKU regardless of capacity.

Answer

Hardcoding credentials in the code.

Question 14

You are using MLflow to track experiments in Azure Machine Learning. You need to log a custom metric that is calculated every 100 iterations. Which MLflow function should you use?

Accepted Answer

'mlflow.log_metric()'.. The 'mlflow.log_metric' function is used to log key-value pairs of metrics, which can be called within the training loop.

Answer

'mlflow.set_tag()'.

Answer

'mlflow.log_artifact()'.

Answer

'mlflow.log_param()'.

Question 15

You want to automate the testing of your prompt flows as part of your CI/CD pipeline. Which tool should you use?

Accepted Answer

Prompt Flow CLI. The 'pf' (Prompt Flow) CLI is designed to run flows and evaluations programmatically in CI/CD pipelines.

Answer

Azure Logic Apps

Answer

Azure Functions

Answer

Azure AI Search test console

Question 16

You are experiencing throttling on your AI endpoint. Which TWO steps should you take?

Accepted Answer

Check current usage against quota limits.. To resolve throttling, you need to either optimize usage or increase the available quota/capacity.

Answer

Disable all security features.

Answer

Change the model version to one that is faster but less smart.

Answer

Delete all existing deployments.

Question 17

You are building a RAG application. Where should you store the indexed documents for optimal retrieval performance?

Accepted Answer

Azure AI Search. Azure AI Search is the native indexer and retriever for AI Foundry RAG applications.

Answer

Azure Blob Storage

Answer

Azure Cache for Redis

Answer

Azure SQL Database

Question 18

Which THREE factors contribute to increased latency in an LLM application?

Accepted Answer

The size/complexity of the chosen model.. Model size, input/output token count, and network transit time are the main drivers of latency.

Answer

The number of system messages used.

Answer

The use of JSON output mode.

Question 19

You want to automate the scaling of your AI agent orchestration. Which TWO components do you need to configure?

Accepted Answer

Autoscale policies.. Auto-scaling is driven by metrics and defined by policies that govern instance counts.

Answer

A manual human-in-the-loop review.

Answer

Hardcoded instance counts.

Answer

Static IP addresses.

Question 20

What is the primary function of a 'Prompt Template' in an Azure AI Prompt Flow?

Accepted Answer

To define the structure of the prompt with dynamic inputs. A prompt template allows users to define the structure of the prompt while injecting dynamic variables.

Answer

To cache previous responses

Answer

To perform load balancing

Answer

To automatically retrain the model