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Microsoft AI-901 Exam Syllabus Topics:
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| Topic 2 |
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NEW QUESTION # 39
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 # 40
What should you use to identify similar faces in a set of images?
- A. Azure OpenAI Service
- B. Azure AI Custom Vision
- C. Azure AI Language
- D. Azure AI Vision
Answer: D
Explanation:
To identify similar faces across different images using Azure, the Azure AI Face service is the most suitable choice. This service leverages AI algorithms to detect, recognize, and analyze human faces, including features like face grouping based on visual similarity.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/find-similar-faces
NEW QUESTION # 41
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 # 42
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 # 43
Stating the source of the data used to train a model is an example of which responsible AI principle?
- A. transparency
- B. privacy and security
- C. reliability and safety
- D. fairness
Answer: A
Explanation:
Transparency in AI refers to openly sharing information about how an AI system is designed, trained, and operates. Stating the source of the data used to train a model is an example of transparency, as it provides clarity about the origins of the data and helps stakeholders understand the model's development process.
NEW QUESTION # 44
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 45
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 # 46
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?
- A. Top P
- B. Model version settings
- C. Temperature
- D. Max Completion Tokens
Answer: D
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 # 47
You are using the Azure Speech SDK to develop a Python application that supports real-time spoken conversations. Which Azure speech class should you use to configure the connection to the Azure Speech service?
- A. AudioConfig
- B. SpeechSynthesizer
- C. AuditOutputConfig
Answer: C
NEW QUESTION # 48
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You use the Azure OpenAI Responses API to send a prompt to the model.
You need to provide an image for analysis.
Which content item should you include in the request?
- A. input_image
- B. output_image
- C. image_generation
- D. image_base64
Answer: A
NEW QUESTION # 49
You deploy the Azure OpenAI service to generate images.
You need to ensure that the service provides the highest level of protection against harmful content.
What should you do?
- A. Configure the Content filters settings
- B. Customize a large language model (LLM)
- C. Configure the system prompt
- D. Change the model used by the Azure OpenAI service
Answer: A
Explanation:
Azure OpenAI, Content filtering
Azure OpenAI includes a content filtering system that works alongside core models, including image generation models. This system works by running both the prompt and completion through a set of classification models designed to detect and prevent the output of harmful content.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/content-filter
NEW QUESTION # 50
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 51
You are using the Azure Speech SDK to develop a Python application that supports real-time spoken conversations.
Which Azure speech class should you use to configure the connection to the Azure Speech service?
- A. AudioConfig
- B. SpeechSynthesizer
- C. AuditOutputConfig
Answer: C
NEW QUESTION # 52
Hotspot Question
You are developing a voice application that listens for spoken commands and converts them into text 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 # 53
What is an example of a Microsoft responsible AI principle?
- A. AI systems should treat people fairly.
- B. AI systems should protect the interests of developers.
- C. AI systems should NOT reveal the details of their design.
- D. AI systems should use black-box models.
Answer: A
Explanation:
Correct:
* AI systems should be secure and respect privacy.
* AI systems should treat people fairly.
Incorrect:
* AI systems should be in the public domain.
* AI systems should make personal details accessible.
* AI systems should NOT reveal the details of their design.
* AI systems should protect the interests of developers.
* AI systems should use black-box models.
Note:
Responsible AI principles
*-> Fairness: AI systems should treat all people fairly.
AI systems should treat everyone equally and provide the same recommendations to all individuals. Fairness in AI systems prevents discrimination based on personal characteristics.
* Reliability and safety: AI systems should perform reliably and safely.
*-> Privacy and security: AI systems should be secure and respect privacy.
* Inclusiveness: AI systems should empower everyone and engage people.
* Etc.
Reference:
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai
NEW QUESTION # 54
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 # 55
Based on the image provided, here is the transcribed text:
You need to build an AI solution that produces new product images based on written descriptions provided by users.
Which AI workload should you use?
- A. image analysis
- B. image generation
- C. object detection
- D. optical character recognition (OCR)
Answer: B
Explanation:
The requirement is to produce new product images based on written descriptions. This is an image generation workload, because the AI system is creating entirely new images from natural language prompts.
NEW QUESTION # 56
You have a Microsoft Foundry project that contains a generative AI model deployment.
You test the model by using the Foundry playground.
You need to develop an application that sends requests to the deployed model.
Which information must the application include to call the model?
- A. The Foundry project display name
- B. The model endpoint and authentication credentials
- C. The exported playground session history
- D. The model training dataset
Answer: B
Explanation:
1. Authentication Data
You must prove your application has permission to access the model. This is included inside the HTTP Headers:
API Key Authentication: Pass the secret key generated by your Foundry project inside the api-key header.
api-key: YOUR_FOUNDRY_SECRET_KEY
Microsoft Entra ID Authentication (Recommended for production): Instead of a static key, pass a dynamic bearer token inside the Authorization header.
Authorization: Bearer YOUR_ENTRA_ACCESS_TOKEN
2. Connection & Routing Data
Your application needs to know exactly where to send the web request. This data is provided via the HTTP Request URL (Endpoint):
Target URI / Base Endpoint: The primary destination host. For standard deployments, it typically aligns with the OpenAI/v1 compatible schema or the generic Azure AI Inference API format.
Deployment Name: Included in either the URL path
(/deployments/{deployment_name}/chat/completions) or inside the request payload body under the "model" parameter to ensure the request is routed to your specific instance.
Reference:
https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/deploy-models-managed
NEW QUESTION # 57
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