AI-102 Plan and manage an Azure AI solution Practice Test 3 — 15 Questions

Question 1

You are designing a document processing pipeline using Azure AI Document Intelligence. The pipeline must extract data from both structured forms and unstructured invoices. The solution should support custom models with minimal manual labeling. Which approach should you use?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Train a custom neural model with a few labeled samples. Azure AI Document Intelligence's custom neural models can be trained with as few as five labeled samples, leveraging transfer learning to achieve high accuracy on both structured forms and unstructured invoices. This approach minimizes manual labeling effort while supporting the diverse document types in the pipeline, unlike prebuilt models that are limited to specific layouts or rule-based methods that require extensive manual configuration.

Answer

Use prebuilt invoice models for all documents

Answer

Use Azure AI Language to analyze text

Answer

Use OCR and custom regex patterns

Question 2

A healthcare organization uses Azure AI Health Insights to analyze patient data. They must ensure that PHI is not logged by the AI services. Which configuration should you apply?

Accepted Answer

Enable diagnostic settings to stream logs to a Log Analytics workspace with a data masking rule. Azure AI Health Insights processes protected health information (PHI), and enabling diagnostic settings to stream logs to a Log Analytics workspace with a data masking rule allows you to redact sensitive PHI from logs before they are stored. Data masking rules in Log Analytics can be configured to hide patterns like patient IDs or names, ensuring compliance with HIPAA while still retaining operational logs.

Answer

Disable all logging for the Azure AI resource

Answer

Configure the resource to use a system-assigned managed identity

Answer

Use Azure Policy to restrict logging to metadata only

Question 3

You are deploying a real-time translation service using Azure AI Translator. The solution must support automatic language detection and translation for customer chat conversations. Which pricing tier should you select to minimize costs while meeting the requirement?

Accepted Answer

Standard S1. The Standard S1 tier (D) is correct because it provides up to 1 million characters per month for translation and language detection, which is sufficient for typical customer chat workloads. The Free tier (F0) is limited to 2,000 characters per request and 2 million characters per month, which may be insufficient for production chat volumes. Higher tiers (S2, S3) offer increased throughput and character limits but incur higher costs, making S1 the most cost-effective choice that meets the requirement.

Answer

Free (F0)

Answer

Standard S3

Answer

Standard S2

Question 4

Which TWO actions are required to enable private endpoint connectivity for an Azure AI Language resource?

Accepted Answer

Disable public network access on the AI resource. Option A is correct because disabling public network access on the Azure AI Language resource ensures that the resource can only be reached through the private endpoint, which is the intended secure configuration for private endpoint connectivity. Option B is correct because a private endpoint is a network interface that must be created in a subnet within a virtual network, which is the fundamental requirement for establishing private connectivity to the Azure AI Language resource. Option C is incorrect because Azure Firewall rules are not required to enable private endpoint connectivity; private endpoints use private IP addresses within the virtual network and do not traverse Azure Firewall by default. Option D is incorrect because while a private DNS zone is often recommended for name resolution, it is not strictly required to enable private endpoint connectivity itself. Option E is incorrect because service tags in network security groups are used for controlling traffic to Azure services, not for enabling private endpoint connectivity.

Answer

Configure an Azure Firewall rule to allow the private endpoint

Answer

Create a private DNS zone for the resource

Answer

Add a service tag to the network security group

Question 5

Which THREE components are part of the Azure AI Foundry SDK for building multi-agent solutions?

Accepted Answer

AIAgentClient. AIAgentClient is correct because it is the Azure AI Foundry SDK component used to create, manage, and invoke agents (including multi-agent orchestration) within a project. AIProjectClient is correct because it is the entry-point client for connecting to an Azure AI Foundry project and obtaining the project-scoped clients, including the agent client. InferenceClient is correct because it is the SDK component used to call the deployed models/agents for inference as part of the multi-agent solution flow. Azure AI Search client and Azure OpenAI client are not part of the Azure AI Foundry SDK's multi-agent building blocks; they are separate service SDKs that may be used alongside it but are not the SDK components in question.

Answer

Azure AI Search client

Answer

Azure OpenAI client

Question 6

Which TWO Azure AI services can be used to build a conversational AI system that handles multi-turn dialogues with context?

Accepted Answer

Azure AI Language. Azure AI Language (B) is correct because it includes Conversational Language Understanding (CLU) and question answering capabilities that let you build conversational systems which track multi-turn dialogue context via intents, entities, and context management. Azure OpenAI Service (C) is correct because its chat completion models (e.g., GPT-4o, GPT-3.5-Turbo) accept a message history array (system/user/assistant roles) that preserves conversational context across turns, enabling multi-turn dialogue. Azure AI Search (A) is a retrieval/indexing service, not a dialogue engine, so it cannot itself manage multi-turn conversations. Azure AI Content Safety (D) only moderates harmful content and does not build or manage dialogues. Azure AI Bot Service (E) is a bot hosting/connector framework, not an AI service that provides the language understanding or generative dialogue modeling needed for context-aware multi-turn conversations.

Answer

Azure AI Search

Answer

Azure AI Content Safety

Answer

Azure AI Bot Service

Question 7

Refer to the exhibit. You are deploying an AI project in Microsoft Foundry using an ARM template. The deployment fails with an error indicating that the hub resource is not in the same region. What is the most likely cause?

Accepted Answer

The hub and project are in different Azure regions. In Azure AI Foundry, the hub and project resources must reside in the same Azure region because the project is a child resource of the hub and relies on the hub's regional endpoint for metadata storage and compute orchestration. The ARM template deployment fails with a region mismatch error when the location property of the project specifies a different region than the hub's location, as Azure enforces regional affinity for child resources to ensure low-latency communication and data residency compliance.

Answer

The resource group for the hub is different from the project's resource group

Answer

The identity type is SystemAssigned, but the hub requires UserAssigned

Answer

The location property is misspelled in the template

Question 8

Refer to the exhibit. A developer creates an agent in Azure AI Foundry with a code_interpreter tool. The agent is supposed to generate plots but returns errors. What is the most likely cause?

Accepted Answer

The JSON syntax is incorrect. The code_interpreter tool in Azure AI Foundry supports common Python visualization libraries such as Matplotlib, Seaborn, and Plotly. Therefore, the error is not due to lack of visualization support. The most likely cause is incorrect JSON syntax in the agent's tool configuration or function call, as JSON formatting errors are a frequent source of failures in Azure AI Foundry agents.

Answer

The instructions are too generic

Answer

The code interpreter tool does not support visualization libraries

Answer

The agent name is invalid

Question 9

You are planning a multi-region deployment of Azure AI services to ensure high availability and low latency for global users. You need to decide how to manage API keys and endpoint URLs across regions. What is the recommended approach?

Accepted Answer

Use Azure API Management to expose a single endpoint that routes to regional Azure AI services resources, each with its own key stored in Key Vault.. It combines Azure API Management as a unified gateway with regional Azure AI Services resources, each secured by individual keys stored in Azure Key Vault. This architecture provides global load balancing, regional failover, and centralized key management without exposing keys in application code. API Management can route requests based on latency or geography, ensuring high availability and low latency while Key Vault rotates keys securely.

Answer

Create separate Azure AI services resources per region and hardcode the keys in application configuration.

Answer

Create a single Azure AI services resource in one region and share the key across all applications.

Answer

Use Microsoft Entra ID authentication with managed identities and have each application call the region-specific endpoint directly.

Question 10

Refer to the exhibit. You are testing a conversational language understanding (CLU) application in Azure AI Language. You send the JSON request to the prediction endpoint and receive a 200 response but with an empty topIntent. What is the most likely cause?

Accepted Answer

The conversationItem is missing a required 'role' field.. B is correct because the JSON request for a conversational language understanding (CLU) application requires a 'role' field within the 'conversationItem' object when using the conversation analysis endpoint. Without this field, the service cannot properly interpret the utterance's context (e.g., user vs. system role), leading to a successful HTTP 200 response but an empty 'topIntent' as the model fails to classify the intent.

Answer

The projectName or deploymentName is incorrect.

Answer

The language parameter is not supported.

Answer

The utterance text is too short.

Question 11

You are responsible for managing costs for Azure AI services used by multiple teams. You notice that costs are higher than expected. Which two actions should you take to reduce costs without impacting performance?

Accepted Answer

Set up budgets and alerts in Cost Management.. Setting up budgets and alerts in Cost Management (Option A) allows you to monitor spending and receive notifications, enabling proactive cost control without impacting performance. Evaluating and choosing the appropriate pricing tier based on usage patterns (Option C) ensures you are not over-provisioned, reducing costs while maintaining performance. Both actions reduce costs without impacting performance.

Answer

Migrate all services to a higher tier for better performance.

Answer

Deactivate unused resources to save costs.

Question 12

You are building a custom copilot using Microsoft Foundry. The copilot must answer questions based on internal documents stored in SharePoint. Which two components are essential for this solution?

Accepted Answer

Azure AI Search with a SharePoint indexer. Azure AI Search with a SharePoint indexer is essential because it ingests and indexes the internal documents from SharePoint, enabling full-text and vector search capabilities that the copilot uses to retrieve relevant content. This indexer automates the crawling of SharePoint sites and keeps the search index synchronized with document changes, which is critical for answering questions based on up-to-date internal data. Additionally, Azure OpenAI Service with a GPT model is necessary to generate natural language answers from the retrieved content, providing the conversational capability of the copilot. Together, they enable the 'retrieve-and-generate' pattern.

Answer

Azure AI Language conversational language understanding (CLU)

Answer

Azure AI Document Intelligence (Form Recognizer)

Question 13

Refer to the exhibit. You run the Azure CLI command to list deleted cognitive services accounts. You need to recover the 'myTextAnalytics' account. Which command should you use?

Accepted Answer

az cognitiveservices account recover --name myTextAnalytics --resource-group <rg> --location eastus. The Azure CLI command `az cognitiveservices account recover` is specifically designed to restore a soft-deleted Cognitive Services account within the 90-day retention period. The command requires the account name, resource group, and location to identify the deleted resource for recovery.

Answer

az cognitiveservices account create --name myTextAnalytics --resource-group <rg> --kind TextAnalytics --location eastus

Answer

az cognitiveservices account restore --name myTextAnalytics --resource-group <rg> --location eastus

Answer

az cognitiveservices account undelete --name myTextAnalytics --resource-group <rg> --location eastus

Question 14

Which TWO are valid techniques for reducing latency in an Azure AI solution that processes real-time chat messages?

Accepted Answer

Deploy Azure AI services in the same region as the application.. Option C is correct because deploying Azure AI services in the same Azure region as the application minimizes network round-trip time (RTT) between the client and the service endpoint, which directly reduces per-request latency for real-time chat. Option D is correct because batching multiple chat messages into a single API call amortizes the per-call network, authentication, and service overhead across several messages, reducing the effective latency per message compared to issuing many individual synchronous calls. Option A is not correct because larger, more accurate models generally increase inference time and cost, raising latency rather than reducing it. Option B is not correct because changing regions to alter pricing tier does not address latency and pricing tiers are not selected by region. Option E is not correct because increasing the client-side timeout only allows more time for slow responses; it does not reduce actual latency and can mask performance problems.

Answer

Use a larger, more accurate model for better performance.

Answer

Move the application to a different region to use a different pricing tier.

Answer

Increase the client-side timeout to allow for slower responses.

Question 15

You are designing a solution that uses Azure AI Document Intelligence to extract data from invoices. The invoices are in various formats (PDF, TIFF, and JPEG) and languages. You need to ensure high accuracy for extraction. Which approach should you take?

Accepted Answer

Use a custom extraction model trained on a sample set of invoices covering all formats and languages.. Azure AI Document Intelligence’s custom extraction models are trained on your specific invoice samples, enabling the model to learn the unique layouts, fields, and languages present across PDF, TIFF, and JPEG formats. This approach directly addresses the need for high accuracy on varied formats and languages, as the model adapts to the exact patterns in your data rather than relying on a generic prebuilt model or brittle post-processing.

Answer

Use the prebuilt invoice model and configure language detection.

Answer

Use Azure AI Vision OCR to extract all text and then parse using regular expressions.

Answer

Convert all invoices to a single format (e.g., PDF) before processing.