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Instant Download Microsoft : AI-103日本語 Questions & Answers as PDF & Test Engine
Updated: Sep 09, 2026
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Microsoft AI-103日本語 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Develop Generative AI Applications and Agents | - Azure OpenAI Service integration
|
| Topic 2: Plan and Manage Azure AI Solutions | - Model selection and lifecycle management - Responsible AI principles and governance - Azure AI resource provisioning and configuration |
| Topic 3: Implement Natural Language Processing Solutions | - Language understanding and intent recognition - Translation and multilingual support - Text analytics and summarization |
| Topic 4: Implement Computer Vision Solutions | - OCR and document intelligence - Image classification and object detection |
| Topic 5: Knowledge Mining and Information Retrieval | - Indexing and semantic search - Azure AI Search configuration - RAG (Retrieval Augmented Generation) patterns |
Microsoft Developing AI Apps and Agents on Azure (AI-103日本語版) Sample Questions:
Microsoft Foundry エージェントが、以下の内容を含む Azure Search インデックスからの応答を解析します。
- 商品名と商品コードを検索できるテキストフィールド
- 製品説明の埋め込みを格納するベクトル場
ユーザーが以下の方法でインデックスを照会できるようにする必要があります。
- 正確な製品名またはコード
- 製品の自然言語による説明
何を設定すればよいですか？
- A. 意味検索のみ
- B. キーワード検索のみ
- C. ハイブリッド検索
- D. ベクター検索のみ
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
エージェントを含む Microsoft Foundry プロジェクトがあり、GitHub リポジトリを使用しています。リポジトリには、エージェントの評価設定を定義する File1 という名前の YAM ファイルが含まれています。プルリクエスト (PR) が開かれたときに File1 で定義された評価を実行する GitHub Actions ワークフローを作成する必要があります。ワークフローはどのように構成すればよいでしょうか？
- A. tenant-id を Microsoft Entra テナント ID に設定します
- B. project-endpoint をプロジェクトのエンドポイントに設定します。
- C. evaluation-config を YAML ファイルのパスに設定します。
- D. model-ployment-name をデプロイされたモデルに設定します。
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
製品に関する質問に回答するSemantic Kernelエージェントがあります。
あなたは、注文状況に関する質問に答えられるように、エージェントの機能を拡張することを計画しています。
エージェントが注文状況に関する質問にできるだけ迅速に回答できるようにする必要があります。また、開発の手間を最小限に抑えるソリューションが求められます。
解決策には何を含めるべきでしょうか？
- A. エージェント
- B. プラグイン
- C. 種子
- D. 関数
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
ホットスポットに関する質問
内部Q&Aエージェントを含むMicrosoft Foundryプロジェクトがあります。
ユーザーがエージェントに質問した際に、以下のような問題が報告されています。
- 次の回答が増加しました：「関連情報なし」
見つかった"
- ピーク時間帯にHTTP 429レート制限超過エラーが定期的に発生
各問題の原因が、モデルの利用不可、リソース制限、または推論の失敗のいずれであるかを特定する必要があります。
どうすればよいですか？回答するには、回答欄で適切な選択肢を選んでください。
注：正解ごとに1ポイントが加算されます。
あなたは、Foundry Tools の Azure Speech を使用して、テキスト ファイル内のスクリプトから指示を読み上げるテキスト読み上げソリューションを構築しています。
解決策が専門用語を誤って発音していることが多いことに気づく。
誤った発音を防ぐ必要があります。解決策は開発の手間を最小限に抑えるものでなければなりません。
あなたはどうすべきでしょうか？
- A. 音声合成マークアップ言語(SSML)を使用して音素を指定します。
- B. 音声合成マークアップ言語 (SSML) を使用して、say をルールとして適用します。
- C. 音声合成マークアップ言語(SSML)を使用して、音声のプロソディを調整します。
- D. Azure OpenAI から Whisper モデルを使用します。
- E. Speech Studioからカスタムニューラル音声をトレーニングします
Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).
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