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| Section | Objectives |
|---|---|
| Topic 1: Implement Natural Language Processing Solutions | - Analyze text using Azure AI Language - Implement question answering and conversational AI - Translate and interpret language using Azure AI services |
| Topic 2: Implement Knowledge Mining and Document Intelligence | - Build Azure AI Search solutions - Enrich and index data for search scenarios - Implement document intelligence solutions |
| Topic 3: Plan and Manage an Azure AI Solution | - Manage security, compliance, and responsible AI - Plan solution requirements and architecture - Select appropriate Azure AI services |
| Topic 4: Implement Generative AI Solutions | - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions |
| Topic 5: Implement Computer Vision Solutions | - Analyze images and videos using Azure AI Vision - Extract information using OCR and form recognition - Implement custom vision models |
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NEW QUESTION # 249
You are developing the knowledgebase by using Azure Cognitive Search.
You need to build a skill that will be used by indexers.
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:
Explanation
Box 1: "categories": ["Locations", "Persons", "Organizations"],
Locations, Persons, Organizations are in the outputs.
Scenario: Contoso plans to develop a searchable knowledgebase of all the intellectual property Note: The categories parameter is an array of categories that should be extracted. Possible category types:
"Person", "Location", "Organization", "Quantity", "Datetime", "URL", "Email". If no category is provided, all types are returned.
Box 2: {"name": " entities"}
The include wikis, so should include entities in the outputs.
Note: entities is an array of complex types that contains rich information about the entities extracted from text, with the following fields name (the actual entity name. This represents a "normalized" form) wikipediaId wikipediaLanguage wikipediaUrl (a link to Wikipedia page for the entity) etc.
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition
NEW QUESTION # 250
You have an Azure subscription that contains an Azure OpenAI resource.
You deploy the GPT-4 model to the resource.
You need to ensure that you can upload files that will be used as grounding data for the model.
Which two types of resources should you create? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,C
Explanation:
Analysis:
Azure AI Bot Service (A): Helps build chatbots but does not store grounding data # # Azure SQL (B): Possible storage, but not recommended for vector search grounding # # Azure AI Document Intelligence (C): Extracts structured info, not used directly for grounding # # Azure Blob Storage (D): Required for storing raw files used in retrieval-augmented generation (RAG) # # Azure AI Search (E): Used to index, vectorize, and query data for grounding # # answer:
D). Azure Blob Storage and E. Azure AI Search
Reference:
Grounding with Azure OpenAI and Azure AI Search
NEW QUESTION # 251
You are developing the knowledgebase by using Azure Cognitive Search.
You need to build a skill that will be used by indexers.
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:
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition
NEW QUESTION # 252
You have an Azure subscription that contains an Azure Al Content Understanding resource named cu1.
You need to create a custom analyzer that will analyze documents.
How should you complete the command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Explanation:
curl -i -X: The POST method is appropriate because you are creating a new custom analyzer, which involves sending a request to create a resource. POST is used for creating new resources in REST APIs.
https:// < cu1 > .services.ai.azure.com/: The base URL should be updated to include the contentunderstanding endpoint, as this is the specific service within the Azure AI Content Understanding resource (cu1) that handles analyzer-related operations. Replace < cu1 > with the actual resource name or endpoint provided by your Azure subscription.
/analyzers/myInvoice7api-version-2024-12-01-preview: This part of the URL is correct as it specifies the endpoint for creating a custom analyzer (/analyzers) with the name myInvoice7 and the API version 2024-12-
01-preview. No changes are needed here, assuming the analyzer name and version are intended as shown.
NEW QUESTION # 253
You have an Azure subscription that contains an Azure AI Content Safety resource named CS1.
You create a test image that contains a circle.
You submit the test image to CS1 by using the curl command and the following command-line parameters.
What should you expect as the output?
Answer: A
Explanation:
The severity levels are from 0 - 7, with 0 being the lowest, if any form of offensive material, and 7 being very naughty/offensive.
NEW QUESTION # 254
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