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| Section | Objectives |
|---|---|
| Implement Computer Vision Solutions | - Implement custom vision models - Extract information using OCR and form recognition - Analyze images and videos using Azure AI Vision |
| Implement Generative AI Solutions | - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions |
| Implement Knowledge Mining and Document Intelligence | - Build Azure AI Search solutions - Enrich and index data for search scenarios - Implement document intelligence solutions |
| Plan and Manage an Azure AI Solution | - Plan solution requirements and architecture - Manage security, compliance, and responsible AI - Select appropriate Azure AI services |
| Implement Natural Language Processing Solutions | - Implement question answering and conversational AI - Analyze text using Azure AI Language - Translate and interpret language using Azure AI services |
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NEW QUESTION # 31
You are building a solution that will detect anomalies in sensor data from the previous 24 hours.
You need to ensure that the solution scans the entire dataset, at the same time, for anomalies.
Which type of detection should you use?
Answer: A
Explanation:
Explanation
Batch anomaly detection is a type of anomaly detection that scans the entire dataset at once for outliers and unusual patterns. Batch anomaly detection is suitable for offline analysis of historical data, such as sensor data from the previous 24 hours. Batch anomaly detection can use various techniques, such as statistical methods, machine learning methods, or hybrid methods, to identify anomalies in the data123.
NEW QUESTION # 32
You are building an agent by using the Azure Al Foundry Agent Service.
You need to ensure that the agent can access publicly accessible data that was released during the past 90 days.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 33
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 34
You have an Azure AI Search solution and a collection of blog posts that include a category field.
You need to index the posts. The solution must meet the following requirements:
- Include the category field in the search results.
- Ensure that users can search for words in the category field.
- Ensure that users can perform drill down filtering based on category.
Which index attributes should you configure for the category field?
Answer: D
Explanation:
Retrievable: Include the category field in the search results.
Searchable: Ensure that users can search for words in the category field.
Facetable: Ensure that users can perform drill down filtering based on category.
https://docs.microsoft.com/en-us/azure/search/search-faceted-navigation
NEW QUESTION # 35
You have the following C# method for creating Azure Cognitive Services resources programmatically.
You need to call the method to create a free Azure resource in the West US Azure region. The resource will be used to generate captions of images automatically.
Which code should you use?
Answer: B
Explanation:
The question is about creating an Azure Cognitive Services resource programmatically with C#.
* Free resource # This requires the F0 (Free) pricing tier.
* West US region # Location should be "westus".
* Generate captions of images automatically # This requires the Computer Vision service.
Key requirements from the question:
* A. create_resource(client, "res1", "ComputerVision", "F0", "westus")
* Uses "ComputerVision" kind # Correct, because Computer Vision provides the image captioning feature.
* Tier is "F0" # Correct, free tier.
* Location "westus" # Correct.
* This is the correct answer.
* B. create_resource(client, "res1", "CustomVision.Prediction", "F0", "westus")
* Custom Vision is for building and deploying custom image classifiers.
* The Prediction resource is specifically for running inference, not general captioning.
* Wrong service for the requirement.
* C. create_resource(client, "res1", "ComputerVision", "S0", "westus")
* "ComputerVision" is correct.
* But "S0" is a paid tier, not the required free tier.
* Does not meet the requirement.
* D. create_resource(client, "res1", "CustomVision.Prediction", "S0", "westus")
* Wrong service (captioning is not handled by Custom Vision).
* Wrong tier (paid instead of free).
* Incorrect.
Option Analysis
The answer: A. create_resource(client, "res1", "ComputerVision", "F0", "westus")
* Azure AI Computer Vision documentation
* Create a Cognitive Services resource in Azure
* Computer Vision capabilities - Image analysis and captioning
Microsoft References
NEW QUESTION # 36
......
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