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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-901 |
| Passing Score: | 700 |
| Exam Price: | $99 USD |
| Real Exam Qty: | 30-40 |
| Exam Format: | Multiple choice, Multiple select, Case studies |
| Certificate Validity Period: | Lifetime |
| Exam Duration: | 60 minutes |
| Available Languages: | Japanese, Korean, German, English, Chinese (Traditional), Spanish, Portuguese (Brazil), Italian, French, Russian, Arabic (Saudi Arabia), Chinese (Simplified), Indonesian (Indonesia) |
| Recommended Training: | Microsoft Learn: AI concepts for developers and technology professionals Microsoft Learn: Get started with Microsoft Foundry |
| Exam Registration: | Pearson VUE Scheduling Microsoft Certification Exam Registration |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No required prerequisites; basic understanding of cloud computing and familiarity with Python syntax recommended |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-901/ |
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NEW QUESTION # 46
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Evaluating model outcomes across demographic groups to reduce bias is an example of the Microsoft responsible AI principle of fairness.
The Microsoft responsible AI principle of fairness means AI systems should treat all people fairly and avoid unfair bias or discrimination across groups.
The other options are incorrect:
accountability means people and organizations remain responsible for AI systems and their effects.
privacy and security focuses on protecting data and controlling access.
transparency means users should understand when and how AI is being used, including system capabilities and limitations.
NEW QUESTION # 47
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 # 48
Drag and Drop Question
Match the description to the corresponding Microsoft Foundry tools.
To answer, drag the appropriate description from the column on the left to its tool on the right.
Each description may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Transcribes spoken input
Speech recognition in Microsoft Foundry transcribes spoken input into text using built-in speech- to-text capabilities.
Transcription FeaturesReal-time transcription: Converts microphone inputs or live audio streams into text instantly.
Batch transcription: Processes pre-recorded audio or video files asynchronously.
Advanced audio models: Leverages tools like GPT-transcribe and GPT-live-transcribe to handle natural speech patterns, numbers, addresses, and industry-specific terminology.
Broad language support: Handles over 140 locales and languages for spoken input.
Box 2: Generates spoken output
Speech synthesis in Microsoft Foundry (via Azure Speech in Foundry Tools) converts text input into realistic, human-like spoken audio output.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-to-text
NEW QUESTION # 49
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: C
NEW QUESTION # 50
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:
Explanation:
Statement 1: In the Foundry playground, you can upload a local image and include text in the same message when prompting a multimodal model. = Yes Microsoft documentation for vision-enabled chat models states that in the chat session pane, you can select the attachment button, upload an image, add a text prompt such as "Describe this image," and then submit it.
Statement 2: When using the OpenAI Responses API and a vision-enabled model, images can be provided only as base64-encoded image data. = No Images are not limited to base64 data. The Responses API supports image input through an image URL, and Azure OpenAI documentation also describes examples using base64 encoded image data.
Statement 3: Prompts that include images require deploying a text-only model because multimodal capabilities are handled by the application layer. = No Image prompts require a vision-enabled multimodal model , not a text-only model. Azure OpenAI vision- capable models accept image and text inputs directly.
NEW QUESTION # 51
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