AI-102 Plan and manage an Azure AI solution Practice Test 7 — 15 Questions

Question 1

You are designing a chatbot using Azure AI Language. The chatbot must understand user intents and also extract entities like dates and locations. Which feature combination should you use?

Accepted Answer

Conversational Language Understanding (CLU) with entities. Conversational Language Understanding (CLU) is the correct Azure AI Language feature for building a chatbot that understands user intents and extracts entities like dates and locations. CLU is specifically designed for natural language understanding (NLU) tasks, providing prebuilt and custom entity extraction alongside intent recognition, which directly matches the requirement.

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Sentiment analysis and entity linking

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Custom text classification and key phrase extraction

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Orchestration Workflow and custom text classification

Question 2

You deployed a custom neural voice in Azure AI Speech. The model generates poor prosody for long sentences. What should you do?

Accepted Answer

Re-record the training audio at 24 kHz sample rate.. A custom neural voice model requires high-quality training data. A 24 kHz sample rate is the standard for Azure AI Speech's neural voices, as it captures the full frequency range needed for natural prosody. Re-recording at this rate ensures the model learns proper intonation and rhythm for long sentences, directly addressing the poor prosody issue.

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Switch to a prebuilt neural voice.

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Increase the number of training scripts.

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Use SSML tags to control prosody at runtime.

Question 3

You need to enforce that only users from your Microsoft Entra ID tenant can call your Azure AI Language API endpoint. Which security mechanism should you configure?

Accepted Answer

Microsoft Entra ID authentication. Microsoft Entra ID authentication (formerly Azure AD) allows you to enforce that only users and applications from your specific Entra ID tenant can call the Azure AI Language API. This is achieved by configuring a managed identity or service principal and assigning it the Cognitive Services User role, which ensures that tokens issued by your tenant are required for access. API keys and IP whitelists do not provide tenant-level identity enforcement, and Azure Firewall is a network-level control that does not authenticate individual users or applications.

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API key authentication

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IP whitelist

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Azure Firewall

Question 4

Your Azure AI Document Intelligence model is failing to extract tables from scanned PDFs. The PDFs are low-quality images. What should you do first?

Accepted Answer

Verify that the Read OCR step is extracting text correctly.. Option A is correct because the Read OCR step is the foundational layer for table extraction in Azure AI Document Intelligence. If the OCR cannot accurately recognize text from low-quality images, subsequent table extraction models will fail regardless of training or image enhancement. Verifying OCR output first isolates whether the issue is at the text recognition stage or the table parsing stage, following a systematic troubleshooting approach.

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Use Azure AI Computer Vision to enhance the image.

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Retrain the model with more table examples.

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Use a higher resolution scanner for input PDFs.

Question 5

You plan to use Azure AI Content Safety to detect hate speech in user-generated content. Which type of content safety is most appropriate for this scenario?

Accepted Answer

Text moderation. Text moderation is the correct choice because Azure AI Content Safety's text moderation API is specifically designed to detect and filter hate speech, along with other harmful content categories like violence and self-harm, in user-generated text. It uses machine learning classifiers trained on a vast corpus to assign severity scores across predefined categories, making it the direct and most appropriate tool for this scenario.

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Custom categories

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Image moderation

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Prompt Shields

Question 6

Your Azure AI Search indexer is failing to index documents from an Azure Blob Storage container. The error message shows 'AccessDenied'. What is the most likely cause?

Accepted Answer

The search service's managed identity lacks 'Storage Blob Data Reader' role.. The 'AccessDenied' error indicates that the Azure AI Search service lacks the necessary permissions to read data from the Azure Blob Storage container. The most likely fix is to assign the 'Storage Blob Data Reader' role to the search service's system-assigned managed identity, which grants read access to blob containers and their contents.

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The blob container name is misspelled in the datasource.

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The indexer execution interval is set too high.

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The index schema does not match the blob metadata.

Question 7

Which TWO actions should you take to ensure your Azure AI Language custom question answering project can be used in a production environment with high availability?

Accepted Answer

Enable multiple read replicas for the knowledge base.. Option A is correct because enabling multiple read replicas for the knowledge base in Azure AI Language custom question answering distributes read traffic across replicas, ensuring high availability and fault tolerance. This is a key production requirement to handle concurrent user queries without a single point of failure.

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Disable redundant infrastructure to optimize performance.

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Use the Free (F0) pricing tier to reduce costs.

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Train the model using only a single language.

Question 8

Which THREE factors should you consider when choosing between Azure AI Document Intelligence prebuilt models and custom models for invoice processing?

Accepted Answer

Prebuilt models require no training data.. Option B is correct because Azure AI Document Intelligence prebuilt models are designed to extract common fields from standard invoice layouts without requiring any labeled training data. They are pretrained on a large corpus of documents, enabling immediate use for typical invoice structures.

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Both model types can be deployed on-premises.

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Prebuilt models are always less accurate than custom models.

Question 9

Which TWO Azure AI services can be used to implement a content moderation pipeline that detects hate speech and blocks violent images?

Accepted Answer

Azure AI Content Safety. Azure AI Content Safety is correct because it is specifically designed to detect hate speech, profanity, and other harmful text content, while Azure AI Vision Image Analysis can analyze images for violent or inappropriate visual content. Together, they form a comprehensive content moderation pipeline that addresses both text and image moderation requirements.

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Azure AI Translator

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Azure AI Speech to Text

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Azure AI Language sentiment analysis

Question 10

Refer to the exhibit. The indexer using this skillset fails with an error that the skill cannot be executed. The Azure Function is deployed and responds correctly when tested directly. What is the most likely cause?

Accepted Answer

The skill endpoint is using HTTP instead of HTTPS.. Azure AI Search indexers that invoke custom skills via Azure Functions require the endpoint to use HTTPS. If the endpoint is configured with HTTP, the indexer will fail with a 'skill cannot be executed' error, even if the function itself works when tested directly. This is because the indexer enforces secure communication to protect data in transit.

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The context is set incorrectly to '/document'.

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The input source '/document/content' is invalid.

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The skill's output targetName does not match the index field.

Question 11

Refer to the exhibit. You deployed this Azure AI Service resource. Developers report that they cannot call the service from their local machines using the API endpoint. The developers are not connected to the corporate VPN. What should you do?

Accepted Answer

Add the developers' public IP addresses to the ipRules list.. The exhibit shows that the Azure AI Service resource's network configuration has 'Selected Networks and Private Endpoints' enabled with a defaultAction of 'Deny'. This means only traffic from explicitly allowed IP addresses or virtual networks can reach the endpoint. Since the developers are not on the corporate VPN, they cannot use a virtual network rule. The correct solution is to add their public IP addresses to the ipRules list, which explicitly permits traffic from those specific IPs while keeping the default deny for all other traffic.

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Disable network ACLs entirely.

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Change defaultAction to Allow and remove all rules.

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Add a second virtual network rule for the developers' subnet.

Question 12

Refer to the exhibit. You are using Azure AI Document Intelligence with a layout model. The pipeline returns an empty tables array even though the document contains tables. The OCR step extracts text correctly. What is the most likely issue?

Accepted Answer

The layout extraction step is not correctly identifying table structures.. The layout model in Azure AI Document Intelligence performs OCR and then uses a layout extraction step to identify structural elements like tables. If the OCR extracts text correctly but the tables array is empty, it indicates that the layout extraction step failed to detect the table boundaries or cell structure, not that OCR missed the text. Option D correctly identifies this as the most likely issue.

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The OCR step is not recognizing table cells.

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The table extraction step is misconfigured.

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The output field mapping for tables is missing.

Question 13

Your organization is deploying Azure AI Document Intelligence to process invoices. You need to ensure that the solution meets compliance requirements by preventing data from being stored outside the European Union. What should you configure?

Accepted Answer

Create the Azure AI Document Intelligence resource in a region within the European Union and configure data residency settings.. Option B is correct because creating the Azure AI Document Intelligence resource in an EU region and configuring data residency settings ensures that all data processed by the service remains within the European Union, meeting compliance requirements. Azure AI Document Intelligence does not automatically guarantee data residency based solely on the resource region; explicit data residency configuration is required to prevent data from being stored or processed outside the specified geographic boundary.

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Deploy Azure AI Document Intelligence in a multi-region configuration across EU datacenters.

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Enable the Resource Firewall on the Azure AI Document Intelligence resource.

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Use a Private Endpoint to connect to the Azure AI Document Intelligence resource.

Question 14

You are using Azure AI Language to perform sentiment analysis on customer feedback. You need to monitor the number of requests sent to the endpoint per minute. Which Azure service should you use?

Accepted Answer

Azure Monitor. Azure Monitor is the correct service because it provides platform metrics, including the 'Requests Per Minute' metric for Azure AI Language endpoints. This metric is automatically collected and can be viewed in the Azure portal, set up alerts on, or queried via the Azure Monitor REST API. It directly answers the need to monitor request rate without additional configuration.

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Azure Cost Management

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Azure Advisor

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Azure Log Analytics

Question 15

Your team is developing a chatbot using Azure AI Bot Service with language understanding via Azure AI Language (CLU). You need to ensure that the chatbot can handle multiple intents in a single user utterance and return confidence scores for each. Which configuration should you use?

Accepted Answer

Use a Conversational Language Understanding (CLU) project with the 'Multiple intents' setting enabled.. Option A is correct because Azure AI Language's Conversational Language Understanding (CLU) supports a 'Multiple intents' setting that allows the model to predict multiple intents from a single utterance, each with its own confidence score. This is the native way to handle multi-intent scenarios without requiring orchestration or custom logic.

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Use an Orchestration workflow project that connects to multiple CLU projects.

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Use a standard CLU project and manually combine intents.

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Use Azure AI QnA Maker with custom logic to detect intents.