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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-901 |
| Exam Format: | Case studies, Multiple choice, Multiple select |
| Available Languages: | Chinese (Traditional), Russian, German, Spanish, Korean, Portuguese (Brazil), English, Indonesian (Indonesia), Italian, Chinese (Simplified), Japanese, Arabic (Saudi Arabia), French |
| Real Exam Qty: | 30-40 |
| Certificate Validity Period: | Lifetime |
| Passing Score: | 700 |
| Exam Price: | $99 USD |
| Exam Duration: | 60 minutes |
| Recommended Training: | Microsoft Learn: AI concepts for developers and technology professionals Microsoft Learn: Get started with Microsoft Foundry |
| Exam Registration: | Microsoft Certification Exam Registration Pearson VUE Scheduling |
| 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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| Topic | Details |
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| Topic 1 |
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| Topic 2 |
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NEW QUESTION # 65
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 66
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: Voice Live returns only transcribed text. = No
Voice Live is not limited to transcription. Microsoft documentation states that the Voice Live API supports real-time bidirectional voice applications, including speech recognition, text-to-speech synthesis, avatar streaming, animation data, and audio processing.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services. = No Voice Live provides a single real-time voice API experience rather than requiring separate STT and TTS implementations for the conversational loop. Microsoft describes live AI voice conversations as combining speech capabilities for real-time interaction, and the Voice Live API includes speech recognition and text-to- speech synthesis features.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This is correct. Microsoft's guidance explains that Azure OpenAI audio/realtime capabilities are for scenarios that combine audio with language understanding, reasoning, or generation in a single model call, and Voice Live supports real-time voice-enabled applications over WebSocket connections.
NEW QUESTION # 67
You are developing an application that analyzes voicemail recordings by using Azure Content Understanding in Foundry Tools.
You need to extract a transcript and structured information from the recordings.
Which type of analyzer should you use?
Answer: D
Explanation:
To extract a transcript and structured information from voicemail recordings, you should use an audio analyzer.In Azure Content Understanding, analyzers are configured based on the type of data being processed. Since voicemail recordings are conversational audio content, an audio analyzer is designed to handle speech-to-text transcription, speaker labeling, and extracting the relevant structured fields.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/audio/overview
NEW QUESTION # 68
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 # 69
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You need to develop an application that sends a message containing text and an image URL.
The solution must ensure the quickest response time.
Which message structure should you include in the request?
Answer: C
Explanation:
For a vision-enabled model, Microsoft documentation shows that multimodal prompts can include both text and image content in the same user message content array. Azure OpenAI vision models accept multimodal image-and-text input and return natural language responses.
The correct request structure is a user message with a content array containing both items, for example:
{
"role": "user",
"content": [
{"type": "input_text", "text": "What is in this image?"}, {"type": "input_image", "image_url":
image_url}
]
}
This avoids sending separate requests and is therefore the best choice for quickest response time.
A and C are incorrect because they send the text and image separately. B is incorrect because the image/question should be sent as a user message, while system messages are used for instructions and behavior.
NEW QUESTION # 70
......
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