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| Section | Weight | Objectives |
|---|---|---|
| Plan and manage an Azure AI solution | 20-25% | - Monitor, optimize, and secure AI solutions - Create and configure Azure AI resources - Select appropriate Microsoft Foundry Services - Plan solutions aligned with responsible AI principles - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select suitable AI models |
| Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection - Implement translation and summarization |
| Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data - Implement intelligent search and retrieval - Build knowledge bases and search indexes |
| Implement computer vision solutions | 10-15% | - Extract text and handwriting from images - Process and index video content - Build and deploy custom vision models - Analyze images and detect objects/features - Integrate vision capabilities into applications |
| Implement an agentic solution | 5-10% | - Understand agent use cases and types - Test, deploy, and optimize agents - Build agents with Microsoft Foundry Agent Service - Develop multi-agent workflows and orchestration |
| Implement generative AI solutions | 15-20% | - Deploy and manage generative models - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers |
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NEW QUESTION # 361
You have a 20-GB video file named File1.avi that is stored on a local drive.
You need to index File1.avi by using the Azure AI Video Indexer website.
What should you do first?
Answer: A
Explanation:
On the Azure AI Video Indexer website, uploading directly from your device is limited to 2 GB -your file is 20 GB , so this won't work. Instead, the recommended approach is to upload the video to an online location and use the "Enter URL" option in the Video Indexer site. The service accepts a direct media-file URL (not a web page like YouTube) and supports uploads up to 30 GB via URL. Given the options provided, OneDrive is the only viable online storage choice listed to host the file before submitting its direct URL to Video Indexer. (Note: the URL must resolve directly to the media file; YouTube links are explicitly not supported, and an Azure Storage queue is not for storing video files.) Microsoft References Azure AI Video Indexer support matrix: 2-GB limit from device; 30-GB limit via URL ; URL must be a direct media file, not a webpage (e.g., YouTube). Microsoft Learn Upload & index media in the Video Indexer website ("Enter URL" flow). Microsoft Learn Considerations at scale: prefer URL upload over byte array; reiterates 2-GB vs 30-GB limits. Microsoft Learn
NEW QUESTION # 362
You plan to build a chatbot to support task tracking.
You create a Conversational Language Understanding service named Iu1.
You need to build a Conversational Language Understanding model to Integrate into the chatbot. The solution must minimize development time to build the model.
Which four 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:
Correct Sequence:
Add the prebuilt domain ToDo
Add a new application
Train the application
Publish the application
Comprehensive Detailed Explanation
You are building a Conversational Language Understanding (CLU) model for a chatbot that supports task tracking. To minimize development time, the best approach is to use a prebuilt domain (like ToDo) instead of building intents/entities manually.
Steps in correct order:
Add the prebuilt domain ToDo
Prebuilt domains in CLU provide ready-to-use intents and entities for common scenarios (e.g., calendar, email, ToDo).
This significantly reduces development time since you don't need to create all intents/entities manually.
Add a new application
You must first create a CLU application that uses the prebuilt domain.
The application acts as the container for intents, entities, and utterances.
Train the application
Training is required after adding intents, entities, and utterances (or using a prebuilt domain).
This ensures the model can classify and extract information correctly.
Publish the application
Once trained, you must publish the application so it can be accessed via an endpoint and integrated into the chatbot.
Incorrect Actions in this Case
Add example utterances # Not required if you're using the prebuilt ToDo domain (utterances are already included).
Correct Sequence:
Add the prebuilt domain ToDo
Add a new application
Train the application
Publish the application
Microsoft References
Conversational Language Understanding (CLU) overview
Prebuilt domains in CLU (LUIS ToDo example)
Train and publish CLU models
NEW QUESTION # 363
You are building a solution that students will use to find references for essays. You use the following code to start building the solution.
For each of the following statements, select Yes is the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statements Analysis
The code will detect the language of documents.
The method used is RecognizeLinkedEntities .
This extracts linked entities and provides Wikipedia references but does not perform language detection.
For language detection, you must call DetectLanguage() .
The Answer: No
The url attribute returned for each linked entity will be a Bing search link.
The RecognizeLinkedEntities API returns a Url property for each entity that points to the Wikipedia page of the entity.
It does not return Bing links.
The Answer: No
The matches attribute returned for each linked entity will provide the location in a document where the entity is referenced.
The matches collection contains objects with offset and length properties, which indicate where in the text the entity appeared.
This is correct.
The Answer: Yes
Verified Answer
The code will detect the language of documents # No
The url attribute returned for each linked entity will be a Bing search link # No The matches attribute returned for each linked entity will provide the location in a document where the entity is referenced # Yes Microsoft References Azure Text Analytics - Recognize linked entities Text Analytics .NET SDK: RecognizeLinkedEntities
NEW QUESTION # 364
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:
Explanation:
To let an agent use public web data with recency controls (e.g., limit to content from the last 90 days), you add the Bing grounding tool. In the Azure AI Foundry Agent Service SDK, you create a connection (e.g., search_connection_id) and then construct a BingGroundingTool with that connection. The tool exposes a list of definitions (tool operations) that the agent can call at runtime.
When creating the agent, you pass tool definitions via the tools= argument (a list of ToolDefinition). The tool_resources= argument is used when the tool requires additional resource descriptors (e.g., Azure AI Search index configuration). For Bing grounding, providing the connection and passing the definitions as tools= is sufficient. This enables the agent to call Bing with date filters to retrieve only recent, publicly accessible content.
Microsoft Azure AI References (titles only)
* Azure AI Agent Service - Bing web grounding tool
* Azure AI Agent Service - Create an agent (agent creation parameters including tools and tool_resources)
* Azure AI Agent Service - Tool connections and definitions
NEW QUESTION # 365
You have the following C# method for creating Azure AI service resources programmatically.
You need to call the function 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: C
Explanation:
There is free tier available for Computer Vision service.
- Free - Web/Container
- 20 per minute
- 5,000 free transactions per month
Only ComputerVision allows you to generate descriptions. Custom vision is used to build custom models for image classification and other basic stuff, not complex tasks like description generation.
Reference:
https://azure.microsoft.com/en-us/pricing/details/cognitive-services/computer-vision/
NEW QUESTION # 366
......
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