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Microsoft AI-103日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement text and speech analysis solutions | 10–15% | - Implement speech capabilities
|
| Topic 2: Implement computer vision solutions | 10–15% | - Build multimodal solutions
|
| Topic 3: Plan and manage Azure AI solutions | 25–30% | - Design Azure AI infrastructure
|
| Topic 4: Implement information extraction and knowledge mining | 10–15% | - Build knowledge bases and search solutions
|
| Topic 5: Implement generative AI and agentic solutions | 30–35% | - Design and implement intelligent agents
|
Microsoft Developing AI Apps and Agents on Azure (AI-103日本語版) Sample Questions:
外部データを取得するためにモデルコンテキストプロトコル(MCP)呼び出しを使用する、Agent1という名前のエージェントがあります。
Agent1が暴力的なコンテンツとしてタグ付けされたコンテンツをMCPサーバーに送信できないように、ガードレールを実装する必要があります。どの介入ポイントを使用すべきでしょうか？
- A. 出力
- B. ユーザー入力
- C. ツール呼び出し
- D. ツールの応答
Correct Answer: C 🗳️
Explanation: Only visible for DumpsReview members. You can sign-up / login (it's free).
検証するためのテストメソッドを開発します。結果は、Foundry Tools API の Azure Vision への呼び出しから取得されます。この呼び出しは、画像内に企業ロゴが存在するかどうかを分析するために使用されます。呼び出しは、brands という名前のブランドのコレクションを返します。
以下のコードセグメントがあります。
以下の各設問について、該当する場合は「はい」を選択してください。該当しない場合は「いいえ」を選択してください。注：正解ごとに1点が加算されます。
Correct Answer:
Explanation:
The first statement is Yes because the conditional expression explicitly requires:
brand.confidence > = 0.75
Only brands meeting or exceeding the 0.75 confidence threshold are printed.
The second statement is Yes . A standard image bounding rectangle exposes x and y as the rectangle ' s origin, corresponding to the upper-left corner. Therefore, printing brand.rectangle.x and brand.rectangle.y provides top-left coordinates.
The third statement is No . The properties w and h represent the width and height of the bounding rectangle, not the absolute x/y coordinates of its lower-right corner.
To obtain the bottom-right coordinates, the application would calculate approximately:
right = x + w
bottom = y + h
Consequently, simply printing (w, h) does not identify the lower-right point despite the wording used in the print statement.
Bounding regions are a common output structure in computer-vision services and must be interpreted correctly when applications overlay detections or validate the physical location of visual entities.
Study Guide alignment: implement solutions that identify objects, components, or regions within images and interpret spatial model outputs . Microsoft Learn
Azure AI を使用してワークスペースの安全性を監視するアプリを開発しています。以下の要件を満たすサービスを推奨する必要があります。
* 従業員が高リスクエリアに入った際にアラートを生成します
* リアルタイムでビデオフィードを監視します
開発作業を最小限に抑える
何をおすすめしますか？
- A. Foundry ToolsのAzure Visionによる空間分析
- B. Azure AI Video Indexer
- C. Azure Custom Vision での物体検出
- D. Foundry Toolsの画像解析におけるAzure Vision
Correct Answer: A 🗳️
Explanation: Only visible for DumpsReview members. You can sign-up / login (it's free).
お客様のAzureサブスクリプションには、以下の構成が含まれています。
* 購読ID: 8d3591aa-96b8-4737-ad09-00f9bled35ad
* テナントID: 3edfe572-cb54-3ced-ael2-c5cl77f39al2
あなたは、感情分析と光学文字認識(OCR)を実行するリソースを作成する予定です。
サブスクリプションにリソースを作成するには、HTTPリクエストを使用する必要があります。ソリューションでは、単一のキーとエンドポイントを使用する必要があります。リクエストをどのように完了すればよいですか？回答するには、回答領域で適切なオプション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:
Azure Resource Manager resource paths are scoped through the subscription , not the Microsoft Entra tenant.
Therefore, the URL must contain:
subscriptions/8d3591aa-96b8-4737-ad09-00f9b1ed35ad
The tenant ID identifies the Microsoft Entra directory but does not replace the subscription portion of an ARM resource path.
The appropriate resource provider is Microsoft.CognitiveServices . Azure AI service accounts, including multi-service Azure AI resources, are provisioned under the Microsoft.CognitiveServices/accounts resource type.
A multi-service resource is required because the solution needs both Language sentiment analysis and Vision OCR while exposing a consolidated Azure resource with common key/endpoint management. Microsoft.
ApiManagement manages API gateways, Microsoft.ContainerService manages Kubernetes services, and Microsoft.KeyVault manages keys and secrets rather than provisioning Azure AI capabilities.
A typical ARM resource path therefore contains:
/subscriptions/ < subscription-id > /resourceGroups/ < rg > /providers/Microsoft.CognitiveServices/accounts/
< name >
This aligns with the AI-103 requirement to design Azure infrastructure for AI apps and choose appropriate Foundry/Azure AI services . Microsoft Learn
Pythonアプリケーションを使用して、REST API経由で顧客サポートのトランスクリプトをFoundry ToolsのAzure Languageに送信することができます。トランスクリプトは英語で、顧客名、メールアドレス、電話番号が含まれる場合があります。
各会話の編集済み記録を保存する必要があります。サポートワークフローでは、顧客名のみを編集し、その他のエンティティタイプは変更しないでください。
分析テキストリクエストの本文はどのように入力すればよいですか？回答するには、回答欄で適切なオプション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:
The operation must use PII Entity Recognition because the required output is a redacted version of the input based on personally identifiable information.
The " kind " property should therefore be set to " PiiEntityRecognition " . The piiCategories parameter restricts which sensitive categories participate in the analysis. Setting it to only [ " Person " ] ensures that recognized customer names are selected while other PII categories-such as PhoneNumber and email-related categories-are not included in the requested PII category set.
This distinction is important because the service supports numerous PII entity categories. Without category restriction, additional sensitive information could be recognized and redacted, which would violate the requirement to leave email addresses and phone numbers unchanged.
EntityRecognition is general Named Entity Recognition and is designed to identify broad entities such as Person, Organization, Location, and DateTime; it is not the specialized redaction operation required here.
LanguageDetection only identifies language.
The resulting PII response can provide redacted text and entity metadata that the application stores or audits.
Study Guide alignment: configure detection of sensitive content and implement solutions that extract entities and structured information from text . Microsoft Learn
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