AI-901日本語受験攻略 & AI-901資格試験

CertShikenのIT専門家は多くの受験生に最も新しいMicrosoftのAI-901問題集を提供するために、学習教材の正確性を増強するために、一生懸命に頑張ります。CertShikenを選ぶなら、君は他の人の一半の努力で、同じMicrosoftのAI-901認定試験を簡単に合格できます。それに、君がMicrosoftのAI-901問題集を購入したら、私たちは一年間で無料更新サービスを提供することができます。

Microsoft AI-901 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals (AI-900) Exam
Exam Number:AI-900
Real Exam Qty:40-60
Certificate Validity Period:Does not expire (Fundamentals certification)
Exam Duration:60 minutes
Available Languages:Japanese, Spanish, Korean, Chinese (Simplified), German, Portuguese (Brazil), Chinese (Traditional), French, English
Passing Score:700 (out of 1000)
Exam Format:Drag and drop, Case study (limited), Multiple response, Multiple choice
Exam Price:Approx. 99 USD (varies by region)
Related Certifications:Microsoft Azure Fundamentals (AZ-900)
Microsoft Azure Data Fundamentals (DP-900)
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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試験の準備方法-一番優秀なAI-901日本語受験攻略試験-ユニークなAI-901資格試験

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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
  • Microsoft Foundry を使用した AI ソリューションの実装: この分野は実践的な内容で、Microsoft Foundry プラットフォームとその関連ツールを使用して AI ソリューションを構築および展開することに重点を置いています。生成型 AI アプリケーション、テキストおよび音声処理、コンピュータ ビジョン、ドキュメント インテリジェンスなど、Foundry ポータルと SDK を通じて実装されるあらゆる分野を網羅しています。
トピック 2
  • AIの概念と機能の特定：この領域では、倫理原則や責任ある設計から、AIモデルの仕組みや実行可能なタスクの種類に至るまで、AIの基礎知識を網羅します。また、生成AI、コンピュータビジョン、音声認識、情報抽出など、AIワークロードの全範囲を探求します。

Microsoft Azure AI Fundamentals 認定 AI-901 試験問題 (Q124-Q129):

質問 # 124
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?

正解：C


質問 # 125
You are developing an application that continuously transcribes speech from a default microphone by using Azure Speech in Microsoft Foundry Tools.
You need to perform speech-to-text transcription from the microphone.
Which Python class should you use?

正解：D

解説：
speechsdk.SpeechRecognizer is the appropriate Python class to handle continuous real-time speech-to-text transcription from a default microphone.
How to Implement It
To achieve continuous transcription (rather than transcribing a single sentence and stopping), you instantiate this class and invoke its asynchronous long-running method.speechsdk.SpeechRecognizer: Acts as the core proxy client connecting your application to the Azure Speech service.
start_continuous_recognition(): The essential method on this class that instructs the SDK to stream microphone data indefinitely and process multi-sentence conversations.
Reference:
https://stackoverflow.com/questions/67691338/continuous-speech-recognition-from-microphone-on-ms-azure


質問 # 126
You have 100 instructional videos that do NOT contain any audio. Each instructional video has a script.
You need to generate a narration audio file for each video based on the script.
Which type of workload should you use?

正解：B


質問 # 127
You are developing a lightweight application that will call an agent programmatically by using the Microsoft Foundry SDK. You need to identify the agent ID. What should you do?

正解：B

解説：
When calling a Foundry agent programmatically by using the Microsoft Foundry SDK, the application needs the agent's configuration values, including the agent ID . The Foundry playground provides a Code view that shows sample application code and environment variables needed to call the agent.
The other options are incorrect:
A). copy the tool name used by the agent identifies a tool, not the agent.
B). copy the model family name identifies the model family, not the agent instance.
C). copy the project name identifies the project, not the specific agent ID.


質問 # 128
Stating the source of the data used to train a model is an example of which responsible AI principle?

正解：B

解説：
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.


質問 # 129
......

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