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Before enrolling in the process of taking the AI-102 exams, candidates should be skilled in implementing Python and C#, using APIs and SDKs based on REST to create natural language processing solutions, computer vision solutions, and knowledge mining and communicative AI solutions based on Azure. In addition, such specialists should be knowledgeable of the elements that create the Azure AI portfolio as well as the data storage options. To add more, they should be able to implement AI principles appropriately.
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement Natural Language Processing Solutions | 20-25% | - Analyze text using Azure AI Language - Create conversational AI solutions with Azure AI Bot Service - Translate text and speech - Build question answering solutions - Implement speech capabilities using Azure AI Speech |
| Topic 2: Implement Generative AI Solutions | 10-15% | - Integrate Azure OpenAI models into applications - Implement prompt engineering techniques - Use Azure OpenAI Service for generative AI - Apply responsible AI practices |
| Topic 3: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Design document processing pipelines - Create custom skills for Azure AI Search - Implement Azure AI Search solutions - Implement semantic and vector search |
| Topic 4: Implement Computer Vision Solutions | 15-20% | - Implement Azure AI Face service - Process video and generate insights - Implement object detection and image classification - Read and process documents using Azure AI Document Intelligence - Analyze images using Azure AI Vision |
| Topic 5: Plan and Manage an Azure AI Solution | 15-20% | - Plan and configure secure AI solutions - Implement governance and compliance for AI solutions - Select appropriate Azure AI services and technologies - Manage AI costs and resource allocation |
| Topic 6: Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Design and implement decision automation - Integrate Azure AI services into applications |
Microsoft Bot Framework SDK を使用してボットを作成します。
カスタムテキスト応答を使用してイベントに応答するようにボットを構成する必要があります。
何を使うべきでしょうか?
Correct Answer: B 🗳️
Explanation: Only visible for TestPDF members. You can sign-up / login (it's free).
カスタム API を使用して、特定の場所の現在の時刻を取得するエージェントを構築しています。
カスタム API の機能をテストする必要があります。
コマンド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。
注意: 正しい選択ごとに 1 ポイントが付与されます。
Correct Answer:
Explanation:
Azure Cognitive Search を使用する Web アプリがあります。
アプリの請求明細を確認したところ、予想よりもはるかに高い請求額が見つかりました。クエリキーが不正使用されたのではないかと疑っています。
検索エンドポイントへの不正アクセスを防ぎ、ユーザーがドキュメントコレクションに対して読み取り専用アクセスのみを行えるようにする必要があります。このソリューションでは、アプリのダウンタイムを最小限に抑える必要があります。
順番に実行する必要がある 3 つのアクションはどれですか。回答するには、適切なアクションをアクション リストから回答領域に移動し、正しい順序に並べます。
Correct Answer:
Explanation:
You are using Azure Cognitive Search, where access is controlled by:
Admin keys: Provide full read/write control (never given to apps).
Query keys: Provide read-only access, meant for client apps.
Here, the query key has been compromised. You want to minimize downtime and ensure continued read-only access.
Step 1 - Add a new query key
First, generate a new query key from the Azure portal or via REST API.
This allows you to continue providing read-only access to authorized apps.
Step 2 - Change the app to use the new key
Update the application configuration so that it authenticates requests with the new query key.
This ensures uninterrupted service while preparing to retire the compromised key.
Step 3 - Delete the compromised key
Once the app is using the new key successfully, revoke the compromised query key.
This prevents further unauthorized usage.
Why not other options?
Regenerate primary/secondary admin key: Not necessary since only the query key is compromised, and admin keys give full control.
Change app to use secondary admin key: Insecure (admin keys should never be exposed to client apps).
Correct Sequence
Add a new query key.
Change the app to use the new key.
Delete the compromised key.
Microsoft References
Manage admin and query keys in Azure Cognitive Search
Create and use query keys
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
注: この問題は、同じシナリオを提示する一連の問題の一部です。一連の問題にはそれぞれ、定められた目標を満たす可能性のある独自の解答が含まれています。問題セットによっては、複数の正解が存在する場合もあれば、正解がない場合もあります。
このセクションの質問に回答した後は、その質問に戻ることはできません。そのため、これらの質問はレビュー画面に表示されません。
vm1 という Azure 仮想マシン上で実行される app1 という Web アプリを作成します。vm1 は、vnet1 という Azure 仮想ネットワーク上にあります。
service1 という名前の新しい Azure Cognitive Search サービスを作成する予定です。
パブリック インターネット経由でトラフィックをルーティングせずに、app1 が service1 に直接接続できることを確認する必要があります。
解決策: service1 とプライベート エンドポイントを vnet1 にデプロイします。
これは目標を満たしていますか?
Correct Answer: A 🗳️
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