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| Section | Weight | Objectives |
|---|---|---|
| Implement Computer Vision Solutions | 15-20% | - Implement Azure AI Face service - Process video and generate insights - Read and process documents using Azure AI Document Intelligence - Analyze images using Azure AI Vision - Implement object detection and image classification |
| Implement Generative AI Solutions | 10-15% | - Apply responsible AI practices - Integrate Azure OpenAI models into applications - Implement prompt engineering techniques - Use Azure OpenAI Service for generative AI |
| Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Design and implement decision automation - Integrate Azure AI services into applications |
| Plan and Manage an Azure AI Solution | 15-20% | - Plan and configure secure AI solutions - Manage AI costs and resource allocation - Implement governance and compliance for AI solutions - Select appropriate Azure AI services and technologies |
| Implement Natural Language Processing Solutions | 20-25% | - Create conversational AI solutions with Azure AI Bot Service - Analyze text using Azure AI Language - Implement speech capabilities using Azure AI Speech - Build question answering solutions - Translate text and speech |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement semantic and vector search - Create custom skills for Azure AI Search - Implement Azure AI Search solutions - Design document processing pipelines |
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NEW QUESTION # 349
You use the Microsoft Bot Framework Composer to build a chatbot that enables users to purchase items.
You need to ensure that the users can cancel in-progress transactions. The solution must minimize development effort.
What should you add to the bot?
Answer: D
NEW QUESTION # 350
You have a web app that uses Azure Cognitive Search.
When reviewing billing for the app, you discover much higher than expected charges. You suspect that the query key is compromised.
You need to prevent unauthorized access to the search endpoint and ensure that users only have read only access to the documents collection. The solution must minimize app downtime.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/search/search-security-api-keys
NEW QUESTION # 351
You are developing a method that uses the Computer Vision client library. The method will perform optical character recognition (OCR) in images. The method has the following code.
During testing, you discover that the call to the GetReadResultAsync method occurs before the read operation is complete.
You need to prevent the GetReadResultAsync method from proceeding until the read operation is complete.
Which two actions should you perform? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
Example code :
do
{
results = await client.GetReadResultAsync(Guid.Parse(operationId));
}
while ((results.Status == OperationStatusCodes.Running ||
results.Status == OperationStatusCodes.NotStarted));
Reference:
https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/dotnet/ComputerVision/ComputerVisionQuickstart.cs
NEW QUESTION # 352
You are developing an application that will use the Computer Vision client library. The application has the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 353
You are building an app that will analyze documents by using the Azure Al Language service.
You need to identify industry-specific technical terms in the documents. The solution must minimize development effort.
What should you use?
Answer: D
Explanation:
You need to identify industry-specific technical terms in documents. That is a classic use case for Custom Named Entity Recognition (custom NER), which lets you build a model to extract domain-specific entities (for example, chemical names, part numbers, contract IDs) from unstructured text. Among the options, only custom NER is designed to recognize entities unique to your domain.
* Why not Key Phrase Extraction? It returns the main concepts/talking points of text, not typed, domain-specific entities.
* Why not CLU? Conversational Language Understanding is for intent and entity extraction from user utterances in conversations, not for mining technical terms from documents. Microsoft Learn
* Why not Language Detection? It detects the language of the text only.
* Custom NER fits: Purpose-built to extract domain-specific entities with minimal code; you label a small dataset and train in Language Studio.
Microsoft References:
* Custom Named Entity Recognition overview - purpose is extracting domain-specific entities.
Microsoft Learn
* Transparency note for custom NER - emphasizes domain-specific extraction. Microsoft Learn
* Key Phrase Extraction overview - identifies main concepts, not domain entities. Microsoft Learn
* CLU overview - intent/entity for conversational scenarios. Microsoft Learn
NEW QUESTION # 354
......
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