AI-901 Exams - Exam AI-901 Syllabus

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

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Exam AI-901 Syllabus | New AI-901 Exam Prep

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Microsoft Azure AI Fundamentals Sample Questions (Q58-Q63):

NEW QUESTION # 58
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You need to create a prompt that ensures the model produces a relevant and useful response.
What should you include in the prompt?

Answer: C

Explanation:
A description of the task must be included in the prompt to ensure the model produces a relevant and useful response.
A prompt's core purpose is to tell the model exactly what it needs to accomplish. To get a useful and relevant output, you must explicitly provide instructions, context, rules, or the objective of the task (such as "extract the total price from this receipt" or "describe the objects in this photo").
Reference:
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/how-to/deploy-foundry-models


NEW QUESTION # 59
You are building a knowledge base by using Azure AI Language service's custom answering feature. Which file format can you use to populate the knowledge base?

Answer: D

Explanation:
Azure AI Language service's custom answering can populate its knowledge base using various file formats, including structured text (.txt, .tsv), Microsoft Office documents (.docx, .xlsx, .pptx), and HTML, PDF, and Markdown files.
Reference:
https://docs.azure.cn/en-us/ai-services/language-service/question-
answering/reference/document-format-guidelines


NEW QUESTION # 60
You are developing an application that converts text into spoken audio and saves the synthesized audio to a file by using Azure Speech in Foundry Tools.
How should you complete the Python code? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 61
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

The completed sentence is:
When developing an AI system for self-driving cars, the Microsoft reliability and safety principle for responsible AI should be applied to ensure consistent operation of the system during use.
Self-driving cars are safety-critical AI systems. The key requirement in the question is consistent operation of the system during use , which maps directly to the Microsoft responsible AI principle of reliability and safety .
The other options are incorrect:
Fairness focuses on reducing bias and treating people equitably.
Accountability focuses on ensuring people remain responsible for AI systems and their outcomes.
Inclusiveness focuses on designing AI systems that work for and empower diverse users, including people with different needs or abilities.
Therefore, the correct answer is reliability and safety .


NEW QUESTION # 62
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 # 63
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