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New Azure AI Engineer Associate AI-102 - Designing and Implementing a Microsoft Azure AI Solution AI-102 Exam Practice Questions

Total 307 Questions

Last Updated On: 3-Oct-2024

Question # 1

You plan create an index for an Azure Cognitive Search service by using the Azure portal. The Cognitive Search service will connect to an Azure SQL database The Azure SQL database contains a table named UserMessages. Each row m User Messages has a field named MessageCopy that contains the text of social media messages sent by a user Users win perform full text searches against the MessageCopy field, and the values of the field will be shown to the users- You need to configure the properties of the index for the MessageCopy field to support the solution. Winch attributes should you enable for the field?
A. Searchable arc Retrievable
B. Sortable and Retrievable
C. Searchable arc Facetable
D. Filterable and Retrievable

Searchable arc Retrievable

Question # 2

You have an Azure Cognitive Search instance that indexes purchase orders by using Form Recognizer You need to analyze the extracted information by using Microsoft Power Bl. The solution must minimize development effort. What should you add to the indexer?
A. a table projection
B. a projection group
C. an object projection
D. a file projection

an object projection

Question # 3

You are developing an application to recognize employees’ faces by using the Face
Recognition API. Images of the faces will be accessible from a URI endpoint.
The application has the following code.

Explanation:
A. True
B. True
C. True
B: see this example code from documentation that uses PersonGroup of size 10,000 :
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/howto-
add-faces
the question wants to trick you into thinking you need to use a LargePersonGroup for a size
of 10,000 - but the documentation for it doesn't include this limitation or criteria:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/howto-
use-large-scale

Question # 4

You are developing a call to the Face API. The call must find similar faces from an existing
list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? To answer, drag the appropriate
values to the correct targets. Each value may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Question # 5

You need to measure the public perception of your brand on social media by using natural language processing. Which Azure service should you use?
A. Language service
B. Content Moderator
C. Computer Vision
D. Form Recognizer

A. Language service

Question # 6

You are developing the document processing workflow. You need to identify which API endpoints to use to extract text from the financial documents. The solution must meet the document processing requirements. Which two API endpoints should you identify? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
A. /vision/v3.2/read/analyzeResults
B. /formrecognizer/v2.0/prebuilt/receipt/analyze
C. /vision/v3.2/read/analyze
D. /vision/v3.2/describe
E. /formercognizer/v2.0/custom/models{modelId}/ analyze

/formrecognizer/v2.0/prebuilt/receipt/analyze

/vision/v3.2/read/analyze

Explanation:
C: Analyze Receipt - Get Analyze Receipt Result.
Query the status and retrieve the result of an Analyze Receipt operation.
Request URL: https://{endpoint}/formrecognizer/v2.0-
preview/prebuilt/receipt/analyzeResults/{resultId}
E: POST {Endpoint}/vision/v3.2/read/analyze
Use this interface to get the result of a Read operation, employing the state-of-the-art
Optical Character Recognition (OCR) algorithms optimized for text-heavy documents.
Scenario: Contoso plans to develop a document processing workflow to extract information
automatically from PDFs and images of financial documents
The document processing solution must be able to process standardized financial documents that have the following characteristics:
- Contain fewer than 20 pages.
- Be formatted as PDF or JPEG files.
- Have a distinct standard for each office.
*The document processing solution must be able to extract tables and text from
the financial documents.
The document processing solution must be able to extract information from receipt
images.
Reference:
https://westus2.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2-
preview/operations/GetAnalyzeReceiptResult
https://docs.microsoft.com/en-us/rest/api/computervision/3.1/read/read

Question # 7

You are building a chatbot by using the Microsoft Bot Framework Composer.
You have the dialog design shown in the following exhibit.

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