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Microsoft AI-103日本語 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Develop Generative AI Applications and Agents | - AI agents architecture
|
| Implement Computer Vision Solutions | - OCR and document intelligence - Image classification and object detection |
| Plan and Manage Azure AI Solutions | - Responsible AI principles and governance - Model selection and lifecycle management - Azure AI resource provisioning and configuration |
| Implement Natural Language Processing Solutions | - Translation and multilingual support - Language understanding and intent recognition - Text analytics and summarization |
| Knowledge Mining and Information Retrieval | - Azure AI Search configuration - Indexing and semantic search - RAG (Retrieval Augmented Generation) patterns |
Microsoft Developing AI Apps and Agents on Azure (AI-103日本語版) Sample Questions:
ドラッグアンドドロップ問題
あなたは、工場生産ラインで製造された不良部品を検出するアプリケーションを開発しています。これらの部品は、あなたのビジネスに特有のものです。
一般的な障害を検出するには、Azure Custom Vision API を使用する必要があります。
どの3つの行動を順番に実行すべきでしょうか？回答するには、行動リストから適切な行動を回答欄に移動させ、正しい順序に並べ替えてください。
Correct Answer:
Explanation:
Step 1: Create a project
You must first set up a new project in the Custom Vision portal or via the SDK to store your data and configuration.
Step 2: Upload and tag images
Next, you need to upload photos of your specific factory components and draw bounding boxes around the faults to tag them.
Step 3: Train the object detection model
Because you need to identify and locate specific, localizable faults on a component, you must train an object detection model rather than a general classifier model.
Reference:
https://thegroundtruth.blog/tag/computervision/
ドラッグアンドドロップ問題
エージェントを含む Microsoft Foundry プロジェクトがあります。このエージェントはスレッドとファイルアップロードを使用し、Azure OpenAI モデルのデプロイメントを呼び出します。
負荷テスト中に、呼び出しが断続的に失敗し、HTTP 429 レート制限超過エラーが返されます。
一部のユーザーによるアップロードが失敗し、HTTP 400 ファイルサイズ超過エラーが発生します。
エラーを軽減し、呼び出しの失敗を減らす必要があります。解決策は、サービスおよびモデルの制限内に収まるものでなければなりません。
各エラーを解決するにはどうすればよいでしょうか？回答するには、適切な操作を正しいエラーにドラッグしてください。各操作は、1回、複数回、またはまったく使用しない場合があります。コンテンツを表示するには、ペイン間の分割バーをドラッグするか、スクロールする必要がある場合があります。
注：彗星の選択はそれぞれ1ポイントです。
Correct Answer:
Explanation:
Box 1: Implement exponential backoff and jitter in the retry logic
To remedy intermittent HTTP 429 rate limit errors while staying within service limits, you must implement a retry policy that uses exponential backoff and jitter.
Because the agent uses threads and file uploads, load testing triggers short-window concurrency spikes (bursting). Azure OpenAI evaluates rate limits in small slices (like 1- to 10-second windows), meaning overlapping file processing or concurrent thread steps will trigger a 429 even if your total Tokens-Per-Minute (TPM) or Requests-Per-Minute (RPM) look safe overall.
Box 2: Split content into smaller files before uploading the files.
Instead of uploading a large document in a single standard files.create request, utilize the Chunked Uploads REST API path. This splits the file payload on your client application layer before streaming it to Azure.
Note: To resolve the HTTP 400 file size exceeded error in your Microsoft Foundry agent, you need to bypass the strict payload constraints of standard single-request uploads. In Azure OpenAI and Microsoft Foundry Agent architectures, a multipart standard upload has a rigid request body limit (typically 30 MB or 50 MB.
Reference:
https://learn.microsoft.com/en-us/answers/questions/2265002/getting-error-after-deployed-a-model-in-azure-ai-f
https://learn.microsoft.com/en-us/answers/questions/5521436/getting-400-error(request-body-too-large)-for-batc
財務チームは、請求書から請求書番号や合計金額などの名前付きフィールドを抽出する必要があり、信頼度の低い値を人間のレビュー担当者に送るために、フィールドごとの信頼度スコアも必要としています。どの Azure Content Understanding モードを使用すべきでしょうか？
- A. 信頼度スコアリングにはAzure AI Document Intelligenceが必要なため、どちらも該当しません。
- B. 標準モード
- C. どちらのモードでも、信頼度スコアが返されるため、どちらでも構いません。
- D. プロモード
Correct Answer: B 🗳️
Explanation: Only visible for LatestCram members. You can sign-up / login (it's free).
Agent1という名前のカスタムエージェントが作成されました。
Microsoft Foundryを使用して、Agent1へのアクセスを制御し、アクティビティを監視する必要があります。
まず最初に何をすべきでしょうか？
- A. Application Insights リソースをプロビジョニングします。
- B. Microsoft Foundry プロジェクトを作成します。
- C. Microsoft Foundry プレイグラウンドに Agent1 を追加します。
- D. Microsoft Foundry プロジェクトに Agent1 を追加します。
Correct Answer: B 🗳️
Explanation: Only visible for LatestCram members. You can sign-up / login (it's free).
あなたは、社内文書の検索にAzure AI Searchを使用するアプリケーションを開発しています。
Azure AI Search では、ドキュメントレベルのフィルタリングを実装する必要があります。
解決策に含めるべき3つの行動はどれですか？それぞれの正解は、解決策の一部を示しています。
注：正解ごとに1ポイントが加算されます。
- A. 検索リクエストとともに、Microsoft Entra ID からアクセストークンを送信します。
- B. ユーザーのグループメンバーシップを取得します
- C. すべてのグループを取得します。
- D. 各インデックスエントリに許可されたグループを追加する
- E. 検索リクエストのフィルタとしてグループを提供する
- F. グループごとに1つのインデックスを作成します。
Correct Answer: B,D,E 🗳️
Explanation: Only visible for LatestCram members. You can sign-up / login (it's free).
