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Microsoft AI-901 Exam Syllabus Topics:

SectionWeightObjectives
Identify AI concepts and responsibilities40-45%- Identify AI model components and configurations
  • 1. Describe data preparation for AI models
  • 2. Describe model training and evaluation concepts
  • 3. Describe model deployment and consumption concepts
- Identify AI concepts and features
  • 1. Describe capabilities of computer vision
  • 2. Describe capabilities of machine learning
  • 3. Describe characteristics of generative AI
  • 4. Describe capabilities of natural language processing
  • 5. Describe types of AI workloads
- Describe principles of responsible AI
  • 1. Describe inclusiveness considerations
  • 2. Describe privacy and security considerations
  • 3. Describe accountability considerations
  • 4. Describe reliability and safety considerations
  • 5. Describe transparency considerations
  • 6. Describe fairness considerations
Implement AI solutions by using Microsoft Foundry55-60%- Implement AI solutions
  • 1. Use code examples to call AI services
  • 2. Integrate AI services into applications
  • 3. Implement single-agent solutions
  • 4. Monitor and manage AI solutions
- Get started with Microsoft Foundry
  • 1. Describe core features and use cases of Microsoft Foundry
  • 2. Create and configure a Foundry project
  • 3. Navigate the Microsoft Foundry portal
- Work with models in Microsoft Foundry
  • 1. Evaluate model performance and safety
  • 2. Customize models with prompt engineering
  • 3. Fine-tune models
  • 4. Discover and deploy foundation models

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Microsoft Azure AI Fundamentals Sample Questions (Q73-Q78):

NEW QUESTION # 73
You are developing an application that analyzes voicemail recordings by using Azure Content Understanding in Foundry Tools.
You need to extract a transcript and structured information from the recordings.
Which type of analyzer should you use?

Answer: B

Explanation:
Voicemail recordings are audio content. Azure Content Understanding analyzers define what type of content to process, including documents, images, audio, or video, and what elements to extract, including transcripts and structured fields.
Microsoft's custom analyzer documentation also shows an audio example based on prebuilt-audio for processing customer support call recordings, which is the same content type as voicemail recordings.
Therefore, to extract a transcript and structured information from voicemail recordings, you should use an audio analyzer.


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

Answer:

Explanation:

Explanation:

A schema defines which fields to extract when analyzing content.
In Azure Content Understanding, the schema or fieldSchema defines the structured data that the analyzer extracts from content, including field names, types, and extraction behavior. Microsoft documentation states that Content Understanding lets you define a schema to extract, classify, or generate field values from unstructured content.
The other options are incorrect:
A keyword list does not define the complete structured output fields.
OCR-only processing extracts text, but it does not define structured fields.
A synchronous API call describes a request pattern, not the extraction schema.


NEW QUESTION # 75
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:


NEW QUESTION # 76
You have a Python application that extracts fields from invoices by using Azure Content Understanding in Foundry Tools.
You submit a PDF for analysis.
What should the application do to retrieve the results?

Answer: A

Explanation:
To retrieve the extraction results using the official azure-ai-contentunderstanding Python SDK, the application must call begin_analyze(), and then call poller.result() to retrieve the results.
Because document analysis is an asynchronous operation, the process is split into initiating the request and waiting for the long-running operation to complete.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api


NEW QUESTION # 77
Based on the image provided, here is the transcribed text:
You need to build an AI solution that produces new product images based on written descriptions provided by users.
Which AI workload should you use?

Answer: B

Explanation:
The requirement is to produce new product images based on written descriptions. This is an image generation workload, because the AI system is creating entirely new images from natural language prompts.


NEW QUESTION # 78
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