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Microsoft AI-102 Exam

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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?



Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-collaborate

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?



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

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:
AI-102_23Q.png related to the Microsoft AI-102 Exam
Image AI-102_23R.png related to the Microsoft AI-102 Exam



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

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?



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

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?



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


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?



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

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?



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

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?



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

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?



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

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:
AI-102_30Q.png related to the Microsoft AI-102 Exam
Image AI-102_30R.png related to the Microsoft AI-102 Exam



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