AI-901過去問無料、AI-901テストサンプル問題

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Microsoft AI-901 認定試験の出題範囲：

トピック出題範囲
トピック 1
  • Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.
トピック 2
  • Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.

>> AI-901過去問無料 <<

AI-901テストサンプル問題、AI-901認定デベロッパー

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Microsoft Azure AI Fundamentals 認定 AI-901 試験問題 (Q74-Q79):

質問 # 74
You are authoring a Conversational Language Understanding application to support a music festival.
You want users to be able to ask questions about scheduled shows, such as: "Which act is playing on the main stage?" The question "Which act is playing on the main stage?" is an example of which type of element?

正解：D


質問 # 75
You are developing an application that converts text into spoken audio and saves the synthesized audio to a file 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.

正解：

解説：

Explanation:
AudioOutputConfig(filename= " output.wav " )
The question specifically states the application must save the synthesized audio to a file . In the Azure Speech SDK for Python, speechsdk.audio.AudioOutputConfig(filename= " output.wav " ) directs the synthesizer to write the generated speech output directly to a WAV file on disk - which is exactly the requirement.
Why the other options are wrong:
* AudioOutputConfig(stream) - This routes audio output to an in-memory audio stream object, not a file. It is used when you want to process or play the audio programmatically without saving it to disk.
* AudioStreamFormat(wave_stream_format=AudioStreamWaveFormat.PCM) - This class defines the format of an audio stream (e.g., PCM encoding, sample rate). It is used when configuring custom audio streams, not when specifying a file output destination. It is not a valid argument for speechsdk.audio. in this context.
The correct and complete line is:
audio_config = speechsdk.audio.AudioOutputConfig(filename= " output.wav " )


質問 # 76
Which type of compute resource should you use to attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning?

正解：A

解説：
To attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning, you should use the "Attached Compute" or "Kubernetes Compute Target". This allows you to leverage your existing AKS cluster as a compute resource for your machine learning tasks within Azure Machine Learning. You can achieve this using the Azure CLI v2, Python SDK v2, or Machine Learning Studio UI.
1. Kubernetes Compute Target:
Azure Machine Learning treats your AKS cluster as a compute target, allowing you to specify it as the location for running your training jobs or deploying models.
2. Attached Compute:
This refers to the ability to connect existing compute resources, like your AKS cluster, to your Azure Machine Learning workspace.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-to-workspace


質問 # 77
You are building an AI solution that processes customer information. Which task is an example of the Microsoft responsible AI principle of privacy and security?

正解：D

解説：
Encrypting stored customer data and restricting system access using role-based controls are exact and correct examples of the Microsoft responsible AI principle of privacy and security.
Key Goals of Privacy and Security
Protect data: Keep user and customer data safe from unauthorized eyes.
Control access: Ensure only the right people use the system.
Build trust: Make users feel secure when they use AI tools.
Reference:
https://www.microsoft.com/en-us/ai/principles-and-approach


質問 # 78
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?

正解：D

解説：
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


質問 # 79
......

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