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Microsoft AI-901 Exam Syllabus Topics:

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

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Microsoft Azure AI Fundamentals Sample Questions (Q50-Q55):

NEW QUESTION # 50
You are developing an application that processes voicemail recordings by using Azure Content Understanding in Foundry Tools. Which feature does Azure Content Understanding use to convert audio to text?

Answer: D

Explanation:
Azure Content Understanding uses transcription to convert audio content, such as voicemail recordings, into text. Microsoft's Azure Content Understanding audio documentation states that transcription converts conversational audio into searchable and analyzable text-based transcripts.


NEW QUESTION # 51
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 # 52
Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: Yes
Yes, a multimodal generative AI model is required to process prompts that contain images. These models can understand and combine different types of data, such as text and visual inputs, at the same time.
Box 2: Yes
Yes, you can use both methods to provide an image in the portal.
In the Microsoft Foundry chat playground, when interacting with vision-enabled models (like gpt-
4o or gpt-4o-mini), the interface allows you to upload local image files directly or paste a publicly accessible URL endpoint.
Box 3: Yes
A multimodal model can interpret multiple images in a single prompt. Most modern vision- language models accept several image inputs at once for tasks like comparison or sequential analysis.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/gpt-with-vision


NEW QUESTION # 53
You are developing an AI-powered customer support application. Which task is an example of the Microsoft responsible AI principle of inclusiveness?

Answer: A

Explanation:
The Microsoft responsible AI principle of inclusiveness means AI systems should be designed to empower and engage everyone, including people with different abilities, languages, and accessibility needs.
Therefore, designing the interface to support multiple languages and screen readers is an example of inclusiveness.


NEW QUESTION # 54
Select the answer that correctly completes the sentence.

Answer:

Explanation:


NEW QUESTION # 55
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