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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Process and index video content - Integrate vision capabilities into applications - Extract text and handwriting from images - Analyze images and detect objects/features - Build and deploy custom vision models |
| Topic 2: Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Implement model monitoring and feedback - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Deploy and manage generative models |
| Topic 3: Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources - Select suitable AI models - Plan solutions aligned with responsible AI principles - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions |
| Topic 4: 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 |
| Topic 5: Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection - Customize and deploy NLP models |
| Topic 6: Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data - Build knowledge bases and search indexes - Implement intelligent search and retrieval |
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NEW QUESTION # 144
You are building a chatbot by using the Microsoft Bot Framework SDK.
You use an object named UserProfile to store user profile information and an object named ConversationData to store information related to a conversation.
You create the following state accessors to store both objects in state.
var userStateAccessors = _userState.CreateProperty < UserProfile > (nameof(UserProfile)); var conversationStateAccessors = _conversationState.CreateProperty < ConversationData > (nameof (ConversationData)); The state storage mechanism is set to Memory Storage.
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:
Explanation:
Box 1: Yes
You create property accessors using the CreateProperty method that provides a handle to the BotState object.
Each state property accessor allows you to get or set the value of the associated state property.
Box 2: Yes
Box 3: No
Before you exit the turn handler, you use the state management objects ' SaveChangesAsync() method to write all state changes back to storage.
Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-v4-state
NEW QUESTION # 145
You have an existing Azure Cognitive Search service.
You have an Azure Blob storage account that contains millions of scanned documents stored as images and PDFs.
You need to make the scanned documents available to search as quickly as possible. What should you do?
Answer: C
Explanation:
To index millions of PDFs/images quickly:
* Partition the blob data into virtual folders (prefixes) and create multiple indexers, one per folder, so they can run in parallel.
* Increase search units (SUs) to raise indexing throughput.
* Schedule the indexers with the same cadence so they run concurrently.Creating multiple services (A, C) is unnecessary and costly. Scheduling sequential execution (B) defeats the goal of "as quickly as possible." References
* Azure Cognitive Search indexer performance guidance: parallelizing blob indexing using multiple indexers over virtual folders/prefixes and scaling SUs for higher throughput.
NEW QUESTION # 146
You have an Azure subscription that contains a Language service resource named ta1 and a virtual network named vnet1. You need to ensure that only resources in vnet1 can access ta1. What should you configure?
Answer: D
Explanation:
To restrict access so that only resources in vnet1 can access the Language service:
You configure the virtual network settings on the Language service resource.
This enables private endpoint integration with the VNet.
NSGs and Azure Firewall apply to subnets/resources but do not configure the service resource itself.
Containers can run Language service locally but are not needed here.
NEW QUESTION # 147
You have an Azure DevOps pipeline named Pipeline1 that is used to deploy an app. Pipeline1 includes a step that will create an Azure AI services account.
You need to add a step to Pipeline1 that will identify the created Azure AI services account. The solution must minimize development effort.
Which Azure Command-Line Interface (CLI) command should you run?
Answer: A
Explanation:
The az cognitiveservices account show command retrieves details about a specified Azure AI Services account, including its properties and settings. By using this command in the Azure DevOps pipeline, you can identify and confirm the details of the Azure AI services account that was created in a previous step.
NEW QUESTION # 148
You are designing a conversation flow to be used in a chatbot.
You need to test the conversation flow by using the Microsoft Bot Framework Emulator.
How should you complete the .chat file? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Graphical user interface, text, application Description automatically generated
Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-add-media-attachments?view=azure-bot-se
NEW QUESTION # 149
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