AI-901 Latest Braindumps & AI-901 Pdf Exam Dump

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Microsoft AI-901 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Identify AI concepts and responsibilities40-45%- Identify AI concepts and features
  • 1. Describe capabilities of computer vision
  • 2. Describe characteristics of generative AI
  • 3. Describe capabilities of natural language processing
  • 4. Describe capabilities of machine learning
  • 5. Describe types of AI workloads
- Describe principles of responsible AI
  • 1. Describe privacy and security considerations
  • 2. Describe fairness considerations
  • 3. Describe transparency considerations
  • 4. Describe reliability and safety considerations
  • 5. Describe inclusiveness considerations
  • 6. Describe accountability considerations
- Identify AI model components and configurations
  • 1. Describe model training and evaluation concepts
  • 2. Describe data preparation for AI models
  • 3. Describe model deployment and consumption concepts
Topic 2: Implement AI solutions by using Microsoft Foundry55-60%- 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
- Work with models in Microsoft Foundry
  • 1. Fine-tune models
  • 2. Customize models with prompt engineering
  • 3. Evaluate model performance and safety
  • 4. Discover and deploy foundation models
- 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

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Microsoft Azure AI Fundamentals Sample Questions (Q112-Q117):

NEW QUESTION # 112
Drag and Drop Question
You are reviewing best practices for using AI at your company.
Which Microsoft responsible AI principle is each task an example of? To answer, drag the appropriate principles to the correct tasks. Each task may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct match is worth one point.

Answer:

Explanation:


NEW QUESTION # 113
Which type of Azure AI workload should you use to create illustrations based on the text of an article?

Answer: C

Explanation:
Using generative AI is a fast and effective way to create illustrations from an article text. Tools like DALL-E 3, Midjourney, and Stable Diffusion can turn written words into custom pictures in seconds.
How to Do It
Copy the main text or a key paragraph from your article.
Write a short prompt that describes the mood, style, and main subject.
Paste your prompt into an AI image tool to generate the art.
Pick the best image and download it for your post.
Reference:
https://dl.gi.de/bitstreams/4d7d68a5-2e94-4994-9f8f-c5119abccd5e/download


NEW QUESTION # 114
You have a Microsoft Foundry project that has a generative AI model deployment.
You need to ensure that responses generated by the model minimize costs and remain within a defined length.
Which parameter should you configure?

Answer: B

Explanation:
To minimize cost and keep generated responses within a defined length, configure Max Completion Tokens.
Microsoft's Azure OpenAI / Foundry API reference defines max_completion_tokens as an upper bound for the number of tokens that can be generated for a completion. Because generated tokens contribute to usage and response length, limiting completion tokens helps control both output length and cost.
Temperature and Top P control randomness or sampling behavior, not maximum response length. Model version settings do not directly define the generated response length.


NEW QUESTION # 115
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable.
This is an example of which Microsoft guiding principle for responsible AI?

Answer: A


NEW QUESTION # 116
You have a website that includes customer reviews.
You need to store the reviews in English and present the reviews to users in their respective language based on each user ' s geographical location.
Which type of natural language processing workload should you use?

Answer: D


NEW QUESTION # 117
......

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