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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Exam Price: | Approx. 99 USD (varies by region) |
| Exam Format: | Drag and drop, Multiple choice, Multiple response, Case study (limited) |
| Available Languages: | Chinese (Simplified), Korean, Chinese (Traditional), Portuguese (Brazil), French, English, Japanese, German, Spanish |
| Passing Score: | 700 (out of 1000) |
| Real Exam Qty: | 40-60 |
| Related Certifications: | Microsoft Azure Fundamentals (AZ-900) Microsoft Azure Data Fundamentals (DP-900) |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Recommended Training: | Azure AI Fundamentals Course Microsoft Learn - AI-900 Learning Path |
| Exam Registration: | Microsoft Certification Portal Schedule exam via Pearson VUE |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online proctored exam or in-person test center |
| Pre Condition: | No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
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NEW QUESTION # 110
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:
Explanation:
Box 1: No
No - Speech synthesis converts spoked audio into written text.
That statement describes speech recognition (or audio transcription), not speech synthesis.
Speech synthesis does the exact opposite: it converts written text into spoken audio.
Box 2: Yes
Yes - Speech recognition can detect and transcribe spoken input.
Speech recognition (also known as automatic speech recognition or speech-to-text) detects acoustic sound waves from spoken input and converts them into written text or actionable digital commands.
Box 3: No
No - Text to speech in Azure Speech in Foundry Tools can translate text input into audible speech in a different language.
That is not entirely correct because Text-to-Speech (TTS) on its own only converts written text into audible speech within the same language; it does not perform language translation.
To translate text input into audible speech in a different language using Azure Speech in Foundry Tools, you must combine or use specific features within the ecosystem:
How Translation Works in Azure Speech
The Translator Tool: If you start with a text input, you must first pass it through the Azure AI Translator (or a foundational Language Model inside Azure AI Foundry) to translate the text from the source language to the target language.
The Text-to-Speech Feature: Once the text is translated, the Text-to-Speech engine synthesizes that translated text into natural-sounding audio using a voice native to the target language.
Speech Translation Feature: If your original input is spoken audio rather than text, Azure Speech offers a dedicated Speech Translation feature. This combines Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-Speech (TTS) into a single workflow to achieve real-time speech-to-speech or speech-to-text translation.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/speech-service/text-to-speech/transparency-note
NEW QUESTION # 111
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 112
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:
Explanation:
Box 1: No
No, batch transcription in Azure Speech does not use a microphone. It processes large volumes of prerecorded audio files stored in locations like Azure Blob Storage.
Box 2: No
No, Azure Speech in Foundry Tools cannot analyze video frames to detect or label objects. It is strictly an audio-focused tool designed for speech-to-text transcription, text-to-speech synthesis, speech translation, and voice analytics Box 3: No No, speech translation in Azure Speech in Foundry Tools outputs translated text as well as optional spoken audio.
Supported Output Formats
Text output: It can output the recognized speech as translated text in one or multiple target languages without generating any spoken audio.
Speech-to-Speech: It can optionally synthesize that translated text into natural-sounding audible speech (audio output) using text-to-speech capabilities.
Source transcription: It simultaneously provides the original source language transcription in text format alongside the translation results.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/speech-service/batch-transcription
https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/speech-service/speech-to-text/transparency-note
NEW QUESTION # 113
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: reliability and safety
When developing an AI system for self-driving cars, the Microsoft __________ principle for responsible AI should be applied to ensure consistent operation of the system during its lifespan.
The Microsoft Reliability and Safety principle for responsible AI should be applied to self-driving cars to ensure consistent operation and mitigate risks. This principle mandates that AI systems must be developed to be dependable and perform as intended, even when facing unexpected situations, making it crucial for a system where a minor error could have severe outcomes.
Consistent operation: Self-driving car AI must operate reliably and consistently under both normal and unexpected conditions.
Robust safety measures: The principle requires rigorous testing and validation to ensure the system responds safely to edge cases and avoids unexpected performance failures.
Preventing harm: The goal is to avoid creating harm by developing the system in alignment with its design ideas and values, which includes resisting manipulation.
Reference:
https://support.microsoft.com/en-us/topic/what-is-responsible-ai-33fc14be-15ea-4c2c-903b-aa493f5b8d92
NEW QUESTION # 114
Which Azure OpenAI model can be used to develop code?
Answer: C
Explanation:
The GPT-4 32k model can be used to develop programming code. It has a large context window, allowing it to process more information and generate more complex code. The model has shown strong performance in coding tasks, even surpassing its predecessor, o3-mini, in some domains.
Reference:
https://vivekupadhyay1.medium.com/openai-chat-gpt-4-32k-detailed-document-ce3486e4786e
NEW QUESTION # 115
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