Microsoft AI-102 Exam Practice Questions (P. 3)
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Question #21
You are building a language model by using a Language Understanding (classic) service.
You create a new Language Understanding (classic) resource.
You need to add more contributors.
What should you use?
You create a new Language Understanding (classic) resource.
You need to add more contributors.
What should you use?
- Aa conditional access policy in Azure Active Directory (Azure AD)
- Bthe Access control (IAM) page for the authoring resources in the Azure portalMost Voted
- Cthe Access control (IAM) page for the prediction resources in the Azure portal
Correct Answer:
B
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-collaborate
B
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-collaborate
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Question #22
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You migrate to a Cognitive Search service that uses a higher tier.
Does this meet the goal?
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You migrate to a Cognitive Search service that uses a higher tier.
Does this meet the goal?
- AYesMost Voted
- BNo
Correct Answer:
A
A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing-based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
A
A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing-based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
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Question #23
DRAG DROP -
You need to develop an automated call handling system that can respond to callers in their own language. The system will support only French and English.
Which Azure Cognitive Services service should you use to meet each requirement? To answer, drag the appropriate services to the correct requirements. Each service may be used once, more than once, or not at all. You may need to drag the split bat between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

You need to develop an automated call handling system that can respond to callers in their own language. The system will support only French and English.
Which Azure Cognitive Services service should you use to meet each requirement? To answer, drag the appropriate services to the correct requirements. Each service may be used once, more than once, or not at all. You may need to drag the split bat between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

Correct Answer:
Box 1: Text Analytics -
The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
Incorrect Answers:
Speaker Recognition which accurately verifies and identifies speakers by their unique voice characteristics.
Box 2: Translator -
Translator is a cloud-based neural machine translation service that is part of the Azure Cognitive Services family of REST APIs. Translator can be used with any operating system and powers many Microsoft products and services used by thousands of businesses worldwide to perform language translation and other language-related operations.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language-detection https://docs.microsoft.com/en-us/azure/cognitive-services/translator/translator-overview

Box 1: Text Analytics -
The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
Incorrect Answers:
Speaker Recognition which accurately verifies and identifies speakers by their unique voice characteristics.
Box 2: Translator -
Translator is a cloud-based neural machine translation service that is part of the Azure Cognitive Services family of REST APIs. Translator can be used with any operating system and powers many Microsoft products and services used by thousands of businesses worldwide to perform language translation and other language-related operations.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language-detection https://docs.microsoft.com/en-us/azure/cognitive-services/translator/translator-overview
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Question #24
You have receipts that are accessible from a URL.
You need to extract data from the receipts by using Form Recognizer and the SDK. The solution must use a prebuilt model.
Which client and method should you use?
You need to extract data from the receipts by using Form Recognizer and the SDK. The solution must use a prebuilt model.
Which client and method should you use?
- Athe FormRecognizerClient client and the StartRecognizeContentFromUri method
- Bthe FormTrainingClient client and the StartRecognizeContentFromUri method
- Cthe FormRecognizerClient client and the StartRecognizeReceiptsFromUri methodMost Voted
- Dthe FormTrainingClient client and the StartRecognizeReceiptsFromUri method
Correct Answer:
D
To analyze receipts from a URL, use the StartRecognizeReceiptsFromUri method
Example code:
private static async Task AnalyzeReceipt(
FormRecognizerClient recognizerClient, string receiptUri)
{
RecognizedFormCollection receipts = await recognizerClient.StartRecognizeReceiptsFromUri(new Uri(receiptUrl)).WaitForCompletionAsync();
Reference:
https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/quickstarts/client-library
D
To analyze receipts from a URL, use the StartRecognizeReceiptsFromUri method
Example code:
private static async Task AnalyzeReceipt(
FormRecognizerClient recognizerClient, string receiptUri)
{
RecognizedFormCollection receipts = await recognizerClient.StartRecognizeReceiptsFromUri(new Uri(receiptUrl)).WaitForCompletionAsync();
Reference:
https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/quickstarts/client-library
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Question #25
You have a collection of 50,000 scanned documents that contain text.
You plan to make the text available through Azure Cognitive Search.
You need to configure an enrichment pipeline to perform optical character recognition (OCR) and text analytics. The solution must minimize costs.
What should you attach to the skillset?
You plan to make the text available through Azure Cognitive Search.
You need to configure an enrichment pipeline to perform optical character recognition (OCR) and text analytics. The solution must minimize costs.
What should you attach to the skillset?
- Aa new Computer Vision resource
- Ba free (Limited enrichments) Cognitive Services resource
- Can Azure Machine Learning Designer pipeline
- Da new Cognitive Services resource that uses the S0 pricing tierMost Voted
Correct Answer:
A
The Computer Vision API uses text recognition APIs to extract and recognize text information from images. Read uses the latest recognition models, and is optimized for large, text-heavy documents and noisy images.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/cognitive-search-with-skillsets
A
The Computer Vision API uses text recognition APIs to extract and recognize text information from images. Read uses the latest recognition models, and is optimized for large, text-heavy documents and noisy images.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/cognitive-search-with-skillsets
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Question #26
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You add indexes.
Does this meet the goal?
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You add indexes.
Does this meet the goal?
- AYes
- BNoMost Voted
Correct Answer:
B
Instead, you could migrate to a Cognitive Search service that uses a higher tier.
Note: A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing- based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
B
Instead, you could migrate to a Cognitive Search service that uses a higher tier.
Note: A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing- based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
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Question #27
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You enable customer-managed key (CMK) encryption.
Does this meet the goal?
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You enable customer-managed key (CMK) encryption.
Does this meet the goal?
- AYes
- BNoMost Voted
Correct Answer:
B
Customer-managed key (CMK) encryption does not affect throttling.
Instead, you could migrate to a Cognitive Search service that uses a higher tier.
Note: A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing- based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
B
Customer-managed key (CMK) encryption does not affect throttling.
Instead, you could migrate to a Cognitive Search service that uses a higher tier.
Note: A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing- based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
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Question #28
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create a web app named app1 that runs on an Azure virtual machine named vm1. Vm1 is on an Azure virtual network named vnet1.
You plan to create a new Azure Cognitive Search service named service1.
You need to ensure that app1 can connect directly to service1 without routing traffic over the public internet.
Solution: You deploy service1 and a private endpoint to vnet1.
Does this meet the goal?
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create a web app named app1 that runs on an Azure virtual machine named vm1. Vm1 is on an Azure virtual network named vnet1.
You plan to create a new Azure Cognitive Search service named service1.
You need to ensure that app1 can connect directly to service1 without routing traffic over the public internet.
Solution: You deploy service1 and a private endpoint to vnet1.
Does this meet the goal?
- AYesMost Voted
- BNo
Correct Answer:
A
A private endpoint is a network interface that uses a private IP address from your virtual network. This network interface connects you privately and securely to a service powered by Azure Private Link. By enabling a private endpoint, you're bringing the service into your virtual network.
The service could be an Azure service such as:
✑ Azure Storage
✑ Azure Cosmos DB
✑ Azure SQL Database
✑ Your own service using a Private Link Service.
Reference:
https://docs.microsoft.com/en-us/azure/private-link/private-endpoint-overview
A
A private endpoint is a network interface that uses a private IP address from your virtual network. This network interface connects you privately and securely to a service powered by Azure Private Link. By enabling a private endpoint, you're bringing the service into your virtual network.
The service could be an Azure service such as:
✑ Azure Storage
✑ Azure Cosmos DB
✑ Azure SQL Database
✑ Your own service using a Private Link Service.
Reference:
https://docs.microsoft.com/en-us/azure/private-link/private-endpoint-overview
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Question #29
You have a Language Understanding resource named lu1.
You build and deploy an Azure bot named bot1 that uses lu1.
You need to ensure that bot1 adheres to the Microsoft responsible AI principle of inclusiveness.
How should you extend bot1?
You build and deploy an Azure bot named bot1 that uses lu1.
You need to ensure that bot1 adheres to the Microsoft responsible AI principle of inclusiveness.
How should you extend bot1?
- AImplement authentication for bot1.
- BEnable active learning for lu1.
- CHost lu1 in a container.
- DAdd Direct Line Speech to bot1.Most Voted
Correct Answer:
D
Inclusiveness: AI systems should empower everyone and engage people.
Direct Line Speech is a robust, end-to-end solution for creating a flexible, extensible voice assistant. It is powered by the Bot Framework and its Direct Line
Speech channel, that is optimized for voice-in, voice-out interaction with bots.
Incorrect:
Not B: The Active learning suggestions feature allows you to improve the quality of your knowledge base by suggesting alternative questions, based on user- submissions, to your question and answer pair. You review those suggestions, either adding them to existing questions or rejecting them.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/direct-line-speech
D
Inclusiveness: AI systems should empower everyone and engage people.
Direct Line Speech is a robust, end-to-end solution for creating a flexible, extensible voice assistant. It is powered by the Bot Framework and its Direct Line
Speech channel, that is optimized for voice-in, voice-out interaction with bots.
Incorrect:
Not B: The Active learning suggestions feature allows you to improve the quality of your knowledge base by suggesting alternative questions, based on user- submissions, to your question and answer pair. You review those suggestions, either adding them to existing questions or rejecting them.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/direct-line-speech
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Question #30
HOTSPOT -
You are building an app that will process incoming email and direct messages to either French or English language support teams.
Which Azure Cognitive Services API should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

You are building an app that will process incoming email and direct messages to either French or English language support teams.
Which Azure Cognitive Services API should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

Correct Answer:
Box 1: api/cognitive.microsofttranslator.com is used for translations.
Incorrect:
eastus.api.cognitive.microsoft.com is used for Face recognition.
Portal.azure.com is the URL of the Azure portal which is a web-based, unified console that provides an alternative to command-line tools. With the Azure portal, you can manage your Azure subscription using a graphical user interface. You can build, manage, and monitor everything from simple web apps to complex cloud deployments.
Box 2: /text/analytics/v3.1/entities/recognition/general
Named Entity Recognition -
The API returns a list of general named entities in a given document.
Request URL: https://{endpoint}/text/analytics/v3.1/entities/recognition/general[?model-version][&showStats][&loggingOptOut][&stringIndexType]
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/translator/reference/v3-0-translate https://westcentralus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v3-1/operations/EntitiesRecognitionGeneral

Box 1: api/cognitive.microsofttranslator.com is used for translations.
Incorrect:
eastus.api.cognitive.microsoft.com is used for Face recognition.
Portal.azure.com is the URL of the Azure portal which is a web-based, unified console that provides an alternative to command-line tools. With the Azure portal, you can manage your Azure subscription using a graphical user interface. You can build, manage, and monitor everything from simple web apps to complex cloud deployments.
Box 2: /text/analytics/v3.1/entities/recognition/general
Named Entity Recognition -
The API returns a list of general named entities in a given document.
Request URL: https://{endpoint}/text/analytics/v3.1/entities/recognition/general[?model-version][&showStats][&loggingOptOut][&stringIndexType]
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/translator/reference/v3-0-translate https://westcentralus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v3-1/operations/EntitiesRecognitionGeneral
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