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Microsoft AI-102日本語 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Exam Format: | Build/review solution scenarios, Multiple response, Case studies, Drag and drop, Multiple choice |
| Exam Price: | USD 165 (varies by country/region) |
| Real Exam Qty: | 40-60 (approximate range) |
| Passing Score: | 700 (out of 1000) |
| Exam Duration: | 100-120 |
| Available Languages: | German, English, Korean, Japanese, Spanish (Latin America), French, Simplified Chinese, Portuguese (Brazil) |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals (AI-900) |
| Certificate Validity Period: | 1 year (renewable annually via Microsoft certification renewal assessment) |
| Recommended Training: | Microsoft Learn AI-102 Learning Path Azure AI Engineer Associate Study Resources |
| Exam Registration: | Microsoft Learn AI-102 Certification Page Microsoft Certification Exam Registration (Pearson VUE) |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored or onsite test center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required, but familiarity with Azure fundamentals and AI/ML concepts is recommended |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/ |
Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Implement Generative AI Solutions | - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions |
| Topic 2: Plan and Manage an Azure AI Solution | - Manage security, compliance, and responsible AI - Select appropriate Azure AI services - Plan solution requirements and architecture |
| Topic 3: Implement Natural Language Processing Solutions | - Translate and interpret language using Azure AI services - Implement question answering and conversational AI - Analyze text using Azure AI Language |
| Topic 4: Implement Computer Vision Solutions | - Analyze images and videos using Azure AI Vision - Implement custom vision models - Extract information using OCR and form recognition |
| Topic 5: Implement Knowledge Mining and Document Intelligence | - Implement document intelligence solutions - Enrich and index data for search scenarios - Build Azure AI Search solutions |
Before You Book the AI-102日本語 Exam: Read These
Currently, the AI-102日本語 exam's passing score is 700 (out of 1000) and the registration fee is USD 165 (varies by country/region). Both are Microsoft's figures and subject to revision — verify them on the official site before you schedule.
Microsoft recommends these official training resources:
Pair whichever course fits your background with regular engine-based practice for the fullest preparation.
Reliability here is built, not claimed. The AI-102日本語 bank is written by a team of IT experts and certified trainers with a wealth of knowledge in the Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) field, and we constantly keep it updated. The online test engine is the signature service: it fits the atmosphere of the actual test in advance, supports Windows, Mac, Android, and iOS, carries no installation limits, and lets you practice anytime, anywhere — perfectly suited to IT workers. Download the free sample first to learn about the product, and know that after purchase you may request the latest version at any time on top of 365 days of automatic updates.
The Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) blueprint covers these core domains:
- Plan and Manage an Azure AI Solution
- Implement Generative AI Solutions
- Implement Knowledge Mining and Document Intelligence
Further domains complete the official outline; the bank addresses every one.
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Microsoft states the following prerequisites for the Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版): No formal prerequisites required, but familiarity with Azure fundamentals and AI/ML concepts is recommended.
Confirm the details on the official certification page before registering.
According to the latest exam information, the AI-102日本語 exam includes 40-60 (approximate range) questions and allows 100-120 minutes. The online engine reproduces those conditions so practice matches the formal test's atmosphere.
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Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) Sample Questions:
あなたはAzureサブスクリプションをお持ちです。
あなたは、Azure AI DALL-E モデルを使用するアプリを開発する予定です。
モデルをデプロイする必要があります。
何を使うべきでしょうか?
- A. Azure SDK for JavaScript および Azure Machine Learning Studio
- B. Azure OpenAI Studio および Azure コマンドラインインターフェイス (CLI)
- C. AzureポータルとMicrosoft Graph API
- D. PythonおよびPowerShellコマンドレット用のAzure SDK
Correct Answer: B 🗳️
Azure Cognitive Search を使用するエンリッチメント パイプラインを作成しています。ナレッジ ストアには、非構造化 JSON データと、テキストを含むスキャンされた PDF ドキュメントが含まれています。
各データ タイプにはどの投影タイプを使用する必要がありますか? 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。
注意: 正しい選択ごとに 1 ポイントが付与されます。
Correct Answer:

Explanation:
Comprehensive Detailed Explanation
In an Azure Cognitive Search knowledge store, you can project enriched content into three main forms:
File projection # For storing binary or unstructured documents (e.g., scanned PDFs, images).
Object projection # For storing JSON objects (hierarchical/unstructured JSON data).
Table projection # For storing structured, tabular results (relational data).
Case 1: JSON data
JSON is already structured/unstructured textual data.
The right projection type for JSON in the knowledge store is Object projection.
Case 2: Scanned data
Scanned PDF/image data is binary file-based content.
The right projection type is File projection, so you can store the original scanned file along with extracted text.
Final Answer (Answer Area)
JSON data: Object projection
Scanned data: File projection
Microsoft References
Azure Cognitive Search knowledge store projections
Object vs File vs Table projections
会話型言語理解(CLA)を用いて言語モデルを構築します。この言語モデルは、Findcontactというインテントを用いて連絡先リストの情報を検索するために用いられます。会話エキスパートが、トレーニングに使用する以下のフレーズリストを提供します。
* ロンドンの連絡先を検索します。
* シアトルで知り合いは誰ですか?
* ウクライナの連絡先を検索します。
会話型言語理解でフレーズ リストを実装する必要があります。
解決策: FindContact インテント内のフレーズごとに新しい発話を作成します。
- A. いいえ
- B. はい
Correct Answer: B 🗳️
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Azure AI Foundryのコンテンツセーフティブロックリストを使用するアプリをお持ちです。
ブロックリストからエントリを削除する必要があります。解決策は、リスト上の既存のエントリへの影響を最小限に抑える必要があります。
コードをどのように完成させればよいでしょうか?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。
Correct Answer:

Explanation:
生産ライン上の不良品を識別するための Azure AI ソリューションを設計しています。
リアルタイムのビデオ フィードと、手動で承認または拒否されるサンプル製品の画像ライブラリがあります。
次の要件を満たすサービスを推奨する必要があります。
ビデオ映像を監視し、不良品を識別します。
画像ライブラリを使用して新しいモデルをトレーニングできます。
開発の労力を最小限に抑えます。
何をお勧めしますか?
- A. Azure AI カスタムビジョン
- B. Azure 機械学習
- C. Azure AI ビデオ インデクサー
- D. Foundry ツールの Azure Vision
Correct Answer: A 🗳️
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