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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 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 capabilities of computer vision
  • 2. Describe capabilities of machine learning
  • 3. Describe capabilities of natural language processing
  • 4. Describe characteristics of generative AI
  • 5. Describe types of AI workloads
- Describe principles of responsible AI
  • 1. Describe inclusiveness considerations
  • 2. Describe privacy and security considerations
  • 3. Describe fairness considerations
  • 4. Describe accountability considerations
  • 5. Describe transparency considerations
  • 6. Describe reliability and safety considerations
Implement AI solutions by using Microsoft Foundry55-60%- Work with models in Microsoft Foundry
  • 1. Discover and deploy foundation models
  • 2. Fine-tune models
  • 3. Evaluate model performance and safety
  • 4. Customize models with prompt engineering
- Implement AI solutions
  • 1. Implement single-agent solutions
  • 2. Monitor and manage AI solutions
  • 3. Integrate AI services into applications
  • 4. Use code examples to call AI services
- 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

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Microsoft Azure AI Fundamentals Sample Questions (Q90-Q95):

NEW QUESTION # 90
You have a Microsoft Foundry project that contains a model deployment.
You are developing an application that sends an image and a user question to the model.
You need to send both text and image content in the same request so the model can return an answer.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets. Each value 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 selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 91
You are developing a lightweight application that will call an agent programmatically by using the Microsoft Foundry SDK.
You need to identify the agent ID.
What should you do?

Answer: B

Explanation:
To determine the agent ID for calling an agent programmatically using the Microsoft Foundry SDK, the correct action is to in the Foundry playground, select Code, and view the .env variables (or look at the code view/overview section showing agent parameters like asst_ID).
When interacting with or testing an agent in the Foundry Playground, clicking the Code view reveals the pre-configured parameters, code snippets, and environment variables (such as the Assistant/Agent ID or project configurations) required to instantiate and call that exact agent programmatically through the SDK.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/code-interpreter


NEW QUESTION # 92
In Azure Machine Learning, what are two ensemble methods for combining models in automated machine learning (automated ML)? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

Answer: B,C

Explanation:
In Azure Machine Learning's automated machine learning (AutoML), two prominent ensemble methods for combining models are Voting and Stacking.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/concept-automated-ml 1


NEW QUESTION # 93
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 # 94
You need to identify harmful content in a generative AI solution that uses Azure OpenAI Service.
What should you use?

Answer: C

Explanation:
Azure AI Content Safety is a new Azure AI Service that can detect harmful user-generated and AI-generated content. This service is being integrated across MS products, including Azure OpenAI Service and Machine Learning prompt flow.
Reference:
https://ivanatilca.medium.com/testing-azure-ai-content-safety-ccd512f9b350


NEW QUESTION # 95
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