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| Section | Weight | Objectives |
|---|---|---|
| Implement Decision Support Solutions | 10-15% | - Integrate Azure AI services into applications - Monitor and optimize decision support solutions - Design and implement decision automation |
| Plan and Manage an Azure AI Solution | 15-20% | - Plan and configure secure AI solutions - Select appropriate Azure AI services and technologies - Manage AI costs and resource allocation - Implement governance and compliance for AI solutions |
| Implement Computer Vision Solutions | 15-20% | - Process video and generate insights - Implement object detection and image classification - Implement Azure AI Face service - Analyze images using Azure AI Vision - Read and process documents using Azure AI Document Intelligence |
| Implement Generative AI Solutions | 10-15% | - Integrate Azure OpenAI models into applications - Use Azure OpenAI Service for generative AI - Implement prompt engineering techniques - Apply responsible AI practices |
| Implement Natural Language Processing Solutions | 20-25% | - Create conversational AI solutions with Azure AI Bot Service - Translate text and speech - Analyze text using Azure AI Language - Build question answering solutions - Implement speech capabilities using Azure AI Speech |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement Azure AI Search solutions - Create custom skills for Azure AI Search - Implement semantic and vector search - Design document processing pipelines |
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NEW QUESTION # 347
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
semi-structured data
The statement is:
" Varying fields for each entity in a JSON document is an example of ______. " Relational data # Stored in structured tables with fixed schema (e.g., SQL database). Not applicable here.
Structured data # Has a strict schema (columns and types are predefined). JSON allows variation, so not structured.
Semi-structured data # Data that does not require a fixed schema, but still uses markers (tags, keys) to separate elements. JSON and XML are classic examples. # Unstructured data # Data without schema or labeling (e.g., videos, images, free text). Not JSON.
Since JSON documents can have varying fields per entity (flexible schema), this is considered semi-structured data.
The Answer: semi-structured data
Microsoft References
Structured, semi-structured, and unstructured data
JSON in Azure
NEW QUESTION # 348
Drag and Drop Question
You have a Docker host named Host1 that contains a container base image.
You have an Azure subscription that contains a custom speech-to-text model named model1.
You need to run model1 on Host1.
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:
https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/speech-container- stt?tabs=container&pivots=programming-language-csharp
NEW QUESTION # 349
You have an app that manages feedback.
You need to ensure that the app can detect negative comments by using the Sentiment Analysis API in Azure Cognitive Service for Language. The solution must ensure that the managed feedback remains on your company's internal network.
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.
NOTE: More than one order of answer choices is correct You will receive credit for any of the correct orders you select.
Answer:
Explanation:
* Provision the Language service resource in Azure.
* Deploy a Docker container to an on-premises server.
* Run the container and query the prediction endpoint.
* According to the Microsoft documentation, the Language service is a cloud-based service that provides various natural language processing features, such as sentiment analysis, key phrase extraction, named
* entity recognition, etc. You can provision the Language service resource in Azure by following the steps in Create a Language resource. You will need to provide a name, a subscription, a resource group, a region, and a pricing tier for your resource. You will also get a key and an endpoint for your resource, which you will use to authenticate your requests to the Language service API.
* According to the Microsoft documentation, you can also use the Language service as a container on your own premises or in another cloud. This option gives you more control over your data and network, and allows you to use the Language service without an internet connection. You can deploy a Docker container to an on-premises server by following the steps in Deploy Language containers. You will need to have Docker installed on your server, pull the container image from the Microsoft Container Registry, and run the container with the appropriate parameters. You will also need to activate your container with your key and endpoint from your Azure resource.
* According to the Microsoft documentation, once you have deployed and activated your container, you can run it and query the prediction endpoint to get sentiment analysis results. The prediction endpoint is a local URL that follows this format: http://<container IP address>:<port>/text/analytics/v3.1-preview.4/sentiment. You can send HTTP POST requests to this endpoint with your text input in JSON format, and receive JSON responses with sentiment labels and scores for each document and sentence in your input.
NEW QUESTION # 350
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a chatbot that uses question answering in Azure Cognitive Service for Language Users report that the responses of the chatbot lark formality when answering spurious questions You need to ensure that the chatbot provides formal responses to spurious questions.
Solution: From Language Studio, you change the chitchat source to qna_chitchit_friindly.tsv. and then retrain and republish the model.
Does this meet the goal?
Answer: B
NEW QUESTION # 351
You build a bot by using the Microsoft Bot Framework SDK.
You need to test the bot interactively on a local machine.
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.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Answer:
Explanation:
Explanation:
The question asks about testing a bot interactively on a local machine when using the Microsoft Bot Framework SDK.
Steps to test locally:
* Build and run the bot
* Compile the bot application code and run it locally (e.g., using Visual Studio or Node.js).
* This exposes the bot's endpoint on localhost (commonly http://localhost:3978/api/messages).
* Open the Bot Framework Emulator
* The Bot Framework Emulator is a desktop app for testing and debugging bots built with the Bot Framework SDK.
* It allows you to send messages to the bot and see the responses.
* Connect to the bot endpoint
* Use the Emulator to connect to the locally running bot by entering its endpoint URL.
* Once connected, you can interact with the bot as if you were a real user.
* Register the bot with the Azure Bot Service # Needed for cloud deployment, not local testing.
* Open the Bot Framework Composer # Only needed if designing the bot with Composer, but this scenario uses the SDK directly.
* Build and run the bot # Open the Bot Framework Emulator # Connect to the bot endpoint
* Test a bot locally with Bot Framework Emulator
* Bot Framework SDK overview
# Final Answer Sequence:
* Build and run the bot
* Open the Bot Framework Emulator
* Connect to the bot endpoint
NEW QUESTION # 352
......
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