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Microsoft AI-901 Exam Syllabus Topics:

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

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Microsoft Azure AI Fundamentals Sample Questions (Q72-Q77):

NEW QUESTION # 72
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:


NEW QUESTION # 73
For each of the following statements, select if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 74
You have 100 instructional videos that do NOT contain any audio. Each instructional video has a script.
You need to generate a narration audio file for each video based on the script.
Which type of workload should you use?

Answer: B


NEW QUESTION # 75
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:


NEW QUESTION # 76
You have the following REST API request.

Which Azure OpenAI model should you use to process the request?

Answer: B

Explanation:
The REST API request contains an image-generation style payload:
{
" prompt " : " A polar bear on the beach holding an icecream " ,
" size " : " 1024x1024 " ,
" n " : 1,
" style " : " vivid "
}
This request asks the model to generate an image from a text prompt. In Azure OpenAI, DALL-E models are used for image generation from natural language prompts.
Why the other options are incorrect:
B). Codex is associated with code generation tasks.
C). GPT-4.1 is primarily used for text/chat and multimodal reasoning, not this classic image-generation API payload.
D). Whisper is used for speech-to-text transcription.


NEW QUESTION # 77
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