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Microsoft AI-901 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.
Topic 2
  • Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.

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Microsoft Azure AI Fundamentals Sample Questions (Q74-Q79):

NEW QUESTION # 74
Select the answer that correctly complete the sentence.

Answer:

Explanation:

Explanation:
Azure Text Analytics client library
Comprehensive and Detailed Explanation with all Azure AI documents : =
The completed sentence is:
To develop an application that analyzes text by using Azure Language in Foundry Tools, use the Azure Text Analytics client library package.
Azure AI Language text analysis features, such as sentiment analysis, named entity recognition, key phrase extraction, language detection, and text summarization, are accessed in code by using the Azure Text Analytics client library .
The other options are incorrect:
Azure AI Projects client library is used for Foundry project and agent-related workflows, not specifically Azure Language text analysis.
Azure OpenAI client library is used to call OpenAI model deployments, not Azure Language text analytics APIs.
Azure Speech SDK is used for speech-to-text and text-to-speech workloads, not text analysis.


NEW QUESTION # 75
You have a Microsoft Foundry project that contains a vision-enabled chat model deployment.
You are developing a Python application that uses the responses API. The application sends a request that includes a user prompt and a local JPEG image.
You need to include the local image in the request.
Which value should you use for the image input?

Answer: D

Explanation:
For a local JPEG image in a Python application using the Azure OpenAI Responses API, the image should be read, base64 encoded, and sent as a data URL, such as:
{ " type " : " input_image " , " image_url " : " data:image/jpeg;base64, < base64_image_data > " } Microsoft's Responses API documentation shows vision-enabled requests using input_image with image_url set to a base64 data URL in the format data:image/jpeg;base64,{base64_image}. It also confirms that JPEG images are supported.
A local file path such as file:///C:/images/photo.jpg or C:\images\photo.jpg is not a valid API-accessible image input. A public or accessible HTTPS URL can be used, but the question specifically says the application sends a local JPEG image , so the correct choice is the base64 data URL.


NEW QUESTION # 76
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:
Box: Azure Speech in Foundry Tools
Azure Speech in Foundry Tools converts spoken audio into text. This specific capability is called speech to text or Automatic Speech Recognition (ASR). It allows you to ingest audio streams or pre-recorded audio files and transcribe them into accurate, searchable text.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-to-text


NEW QUESTION # 77
Hotspot Question
Select the answer that correctly complete the sentence.

Answer:

Explanation:


NEW QUESTION # 78
Select the answer that correctly completes the sentence.

Answer:

Explanation:


NEW QUESTION # 79
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