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Microsoft AI-901日本語 Exam Syllabus Topics:
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Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-901
Microsoft Azure AI Fundamentals (AI-901日本語版) Sample Questions:
文を正しく完成させる選択肢を選びなさい。
Correct Answer:
Explanation:
The correct answer is classify email messages as work-related or personal . Natural language processing (NLP) is concerned with analyzing, interpreting, and processing human language, including unstructured text contained in documents, messages, reviews, and emails. Text classification is therefore a direct NLP workload: an AI model analyzes the linguistic content of an email and assigns it to a predefined category such as work-related or personal .
Microsoft ' s current AI-901 study guide explicitly requires candidates to identify scenarios for common AI workloads, including text analysis , and to understand common text-analysis techniques. Microsoft Azure Language in Foundry Tools similarly supports capabilities for extracting information from text and classifying text , demonstrating that categorization based on textual content is an NLP function.
Predicting future car rentals is primarily a regression/forecasting problem because the output is a numerical quantity. Predicting whether a website visitor will transact is typically a binary classification machine- learning problem based on behavioral or transactional features, not necessarily language. Stopping industrial machinery when a temperature threshold is exceeded is a rule-based monitoring/control scenario.
生成型AIモデルをデプロイしたMicrosoft Foundryプロジェクトをお持ちです。
モデルによって生成される応答がコストを最小限に抑え、かつ定義された長さ内に収まるようにする必要があります。
どのパラメータを設定すればよいですか？
- A. 最大完了トークン
- B. 温度
- C. モデルバージョン設定
- D. トップP
Correct Answer: A 🗳️
Explanation: Only visible for UpdateDumps members. You can sign-up / login (it's free).
画像からテキストを抽出することは、どのタイプのAI機能の例ですか？
- A. テキスト分析
- B. 光学文字認識(OCR)
- C. 物体検出
- D. 画像の説明
Correct Answer: B 🗳️
Explanation: Only visible for UpdateDumps members. You can sign-up / login (it's free).
提供された画像に基づいて、以下にテキストを書き起こします。
ユーザーが入力した説明文に基づいて、新しい製品画像を生成するAIソリューションを構築する必要があります。
どのAIワークロードを使用すべきでしょうか？
- A. 画像解析
- B. 光学文字認識(OCR)
- C. 物体検出
- D. 画像生成
Correct Answer: D 🗳️
Explanation: Only visible for UpdateDumps members. You can sign-up / login (it's free).
以下の各記述について、正しい場合は「はい」を選択してください。そうでない場合は「いいえ」を選択してください。
注：正解ごとに1ポイントが加算されます。
Correct Answer:
Explanation:
Statement 1: Evaluators in Microsoft Foundry replace the need for configuring token limits. = No Evaluators are used to assess model or agent output quality, safety, and reliability. They do not replace model configuration settings such as token limits. Microsoft describes evaluators as tools that measure the quality, safety, and reliability of AI responses.
Statement 2: Evaluators in Microsoft Foundry can assess the quality and safety of responses generated by a generative AI model. = Yes This is correct. Microsoft Foundry includes built-in evaluators for general quality metrics such as coherence and fluency, safety/security metrics, RAG metrics, and agent-specific metrics.
Statement 3: Evaluators in Microsoft Foundry can retrain a deployed generative AI model automatically when quality issues are detected. = No Evaluators measure and report quality, safety, and reliability issues. They do not automatically retrain deployed generative AI models. Microsoft describes evaluation as measuring model or agent performance against test data, while monitoring can alert when outputs fail quality thresholds.
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