Free PDF Newest AI-102 - Designing and Implementing a Microsoft Azure AI Solution Reliable Test Objectives

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Microsoft AI-102 Exam Syllabus Topics:

Section	Weight	Objectives
Implement Computer Vision Solutions	15-20%	- Read and process documents using Azure AI Document Intelligence - Implement Azure AI Face service - Implement object detection and image classification - Process video and generate insights - Analyze images using Azure AI Vision
Implement Decision Support Solutions	10-15%	- Design and implement decision automation - Monitor and optimize decision support solutions - Integrate Azure AI services into applications
Plan and Manage an Azure AI Solution	15-20%	- Manage AI costs and resource allocation - Plan and configure secure AI solutions - Select appropriate Azure AI services and technologies - Implement governance and compliance for AI solutions
Implement Knowledge Mining and Document Intelligence Solutions	15-20%	- Implement semantic and vector search - Create custom skills for Azure AI Search - Design document processing pipelines - Implement Azure AI Search solutions
Implement Generative AI Solutions	10-15%	- Use Azure OpenAI Service for generative AI - Apply responsible AI practices - Integrate Azure OpenAI models into applications - Implement prompt engineering techniques
Implement Natural Language Processing Solutions	20-25%	- Implement speech capabilities using Azure AI Speech - Create conversational AI solutions with Azure AI Bot Service - Analyze text using Azure AI Language - Build question answering solutions - Translate text and speech

>> AI-102 Reliable Test Objectives <<

Microsoft AI-102 Dumps & AI-102 Cert Guide

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Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q297-Q302):

NEW QUESTION # 297
You have a chatbot.
You need to test the bot by using the Bot Framework Emulator. The solution must ensure that you are prompted for credentials when you sign in to the bot.
Which three settings should you configure? To answer, select the appropriate settings in the answer area.
NOTE Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
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NEW QUESTION # 298
You are building content for a video training solution.
You need to create narration to accompany the video content. The solution must use Custom Neural Voice.
What should you use to create a custom neural voice, and which service should you use to generate the narration? To answer, select the appropriate options in the answer area.
NOTE: Each correct answer is worth one point.

Answer:

Explanation:

Explanation

NEW QUESTION # 299
You build a chatbot by using Azure OpenAI Studio.
You need to ensure that the responses are more deterministic and less creative.
Which two parameters should you configure? To answer, select the appropriate parameters in the answer area.
NOTE: Each correct answer is worth one point.

Answer:

Explanation:

Explanation:

NEW QUESTION # 300
You are developing a method that uses the Computer Vision client library. The method will perform optical character recognition (OCR) in images. The method has the following code.

During testing, you discover that the call to the GetReadResultAsync method occurs before the read operation is complete.
You need to prevent the GetReadResultAsync method from proceeding until the read operation is complete.
Which two actions should you perform? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.

A. Add code to verify the results.Status value.
B. Remove the Guid.Parse(operationId) parameter.
C. Add code to verify the status of the txtHeaders.Status value.
D. Wrap the call to GetReadResultAsync within a loop that contains a delay.

Answer: A,D

Explanation:
Explanation
Example code :
do
{
results = await client.GetReadResultAsync(Guid.Parse(operationId));
}
while ((results.Status == OperationStatusCodes.Running ||
results.Status == OperationStatusCodes.NotStarted));
Reference:
https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/dotnet/ComputerVision/Comp

NEW QUESTION # 301
You are building a Language Understanding solution.
You discover that many intents have similar utterances containing airport names or airport codes.
You need to minimize the number of utterances used to fram the model.
Which type of custom entity should you use?

A. list
B. Pattera.any
C. regular expression
D. machine-learning

Answer: A

Explanation:
When many utterances differ only by airport names or codes, you don't want to list them all.
A Pattern.any entity acts as a placeholder for free-form input inside patterns, allowing the model to accept any word/phrase in that slot.
Machine-learning entities require lots of labeled utterances.
List entities work for fixed sets (e.g., specific known airport codes), but this scenario implies dynamic airport data.
Regex entities are for structured formats (like postal codes).

NEW QUESTION # 302
......

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