AI-102 Practice Test 8 — 10 Questions

Question 1

A healthcare organization is deploying an Azure AI Document Intelligence solution to extract medical record data. The solution must comply with HIPAA and process sensitive patient data. The data must be encrypted at rest and in transit, and access must be audited. The solution will be used by multiple departments, each requiring different levels of access. Which combination of Azure services should the architect recommend?

Accepted Answer

Azure AI Document Intelligence with private endpoints, managed identity authentication, Azure Storage with customer-managed keys (CMK), and Azure RBAC for access control.. Option C is correct because it ensures HIPAA compliance by using private endpoints to keep traffic within the Azure backbone network, managed identity for secure authentication without storing credentials, customer-managed keys (CMK) for encryption at rest with full control over key rotation, and Azure RBAC to enforce least-privilege access across departments. This combination addresses encryption in transit (private endpoint + HTTPS), encryption at rest (CMK), and audited access (RBAC + Azure Monitor).

Answer

Azure AI Document Intelligence with public endpoint, Azure AD authentication, and Azure Storage with customer-managed keys (CMK).

Answer

Azure AI Document Intelligence with public endpoint, Azure AD authentication, and Azure Storage with encryption at rest using Microsoft-managed keys.

Answer

Azure AI Document Intelligence with service endpoints, shared access signature (SAS) tokens, and Azure Storage with encryption at rest using Microsoft-managed keys.

Question 2

You are developing a content moderation solution that uses Azure Content Moderator to review images uploaded by users. The solution must flag images for potential adult content. Which TWO actions should you take to achieve this goal?

Accepted Answer

Configure a human review loop using the Review tool. Option C is correct because Azure Content Moderator's Review tool enables human-in-the-loop review, which is essential for accurately flagging adult content when automated confidence scores are borderline. This allows human moderators to confirm or override the automated classification, ensuring compliance with content policies. Option D is correct because the Evaluate operation on the image endpoint directly analyzes images for adult and racy content using pre-trained models, returning a confidence score that can trigger further action.

Answer

Train a custom image classifier using Content Moderator's training API

Answer

Use the List Management API to add images to a blocklist

Answer

Use the OCR operation to extract text from images

Question 3

Which TWO actions should you take to reduce the latency of an Azure AI Computer Vision OCR call on a large image?

Accepted Answer

Resize the image to a smaller resolution before calling the API.. Options B and D are correct. B: Resizing reduces processing time. D: Using the Read API asynchronously allows the client to poll, avoiding timeout. A: Increasing timeout doesn't reduce latency. C: Using CPU doesn't help. E: Cognitive Services container on-premises might add network latency.

Answer

Use a CPU-bound compute instance.

Answer

Increase the API timeout value.

Answer

Deploy the Cognitive Services container on-premises.

Question 4

Refer to the exhibit. You have a skillset with two skills. You run the indexer and find that the output field 'organizations' is empty for documents that clearly contain organization names. The 'keyPhrases' output is populated correctly. What is the most likely cause of the issue?

Accepted Answer

The skill is not configured with a 'defaultLanguageCode' and the documents are not in English.. The 'keyPhrases' output is populated correctly, indicating the text extraction and overall pipeline are functional. The Entity Recognition skill requires a 'defaultLanguageCode' to correctly identify entities; if it is not set and the documents are not in English, the skill may fail to extract organizations, resulting in an empty 'organizations' field. This is a known behavior where the skill defaults to English and cannot process other languages without explicit configuration.

Answer

The skill's 'name' property is set to '#1', which is invalid.

Answer

The 'categories' property is misspelled; it should be 'entityCategories'.

Answer

The input source '/document/content' is incorrect; it should be '/document/text'.

Question 5

Match each Azure Bot Service channel to its description.

Question 6

Match each Azure AI feature to the service that provides it.

Question 7

Which TWO actions should you take to ensure compliance with data privacy regulations when using Azure AI Language to process customer support transcripts that contain personally identifiable information (PII)?

Accepted Answer

Enable PII detection and redaction in the Azure AI Language service.. Option D is correct because Azure AI Language's PII detection and redaction feature is specifically designed to identify and mask personally identifiable information (PII) in text, such as names, addresses, and social security numbers, directly within the service. This built-in capability ensures that sensitive data is removed or obfuscated before storage or further processing, directly supporting compliance with data privacy regulations like GDPR or HIPAA.

Answer

Disable diagnostic logging for the resource.

Answer

Use customer-managed keys (CMK) for encryption.

Answer

Apply Azure AI Content Safety filters to anonymize personal data.

Question 8

Refer to the exhibit. You have created a Text Analytics resource and retrieved its keys. You want to use the key1 to call the Sentiment Analysis API from a Python application. Which endpoint URL should you use?

Accepted Answer

https://mytextanalytics.cognitiveservices.azure.com/text/analytics/v3.1/sentiment. The exhibit shows the endpoint is https://mytextanalytics.cognitiveservices.azure.com/. For Text Analytics, the sentiment endpoint is appended with /text/analytics/v3.1/sentiment. The correct URL is https://mytextanalytics.cognitiveservices.azure.com/text/analytics/v3.1/sentiment.

Answer

https://mytextanalytics.cognitiveservices.azure.com/sentiment/v3.1

Answer

https://mytextanalytics.api.cognitive.microsoft.com/text/analytics/v3.1/sentiment

Answer

https://mytextanalytics.cognitiveservices.azure.com/analyze

Question 9

Refer to the exhibit. You called the Key Phrase Extraction API on two documents. What is the total number of key phrases extracted?

Accepted Answer

5. Document 1 has 3 key phrases: Azure, NLP, services. Document 2 has 2 key phrases: Microsoft, AI. Total is 5.

Answer

7

Answer

3

Answer

2

Question 10

Refer to the exhibit. You deployed a custom model for Language service. Which command should you run to check if the deployment is ready to accept inference requests?

Accepted Answer

az cognitiveservices account deployment show --resource-group myRG --name myLangService --deployment-name myDeployment. The show command confirms provisioningState is Succeeded, indicating readiness. The create command only returns the initial status.

Answer

az cognitiveservices account deployment list --resource-group myRG --name myLangService

Answer

az cognitiveservices account deployment delete --resource-group myRG --name myLangService --deployment-name myDeployment

Answer

az cognitiveservices account deployment create --resource-group myRG --name myLangService --deployment-name myDeployment