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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and Manage an Azure AI Solution | 15-20% | - Manage AI costs and resource allocation - Select appropriate Azure AI services and technologies - Implement governance and compliance for AI solutions - Plan and configure secure AI solutions |
| Topic 2: Implement Computer Vision Solutions | 15-20% | - Analyze images using Azure AI Vision - Read and process documents using Azure AI Document Intelligence - Implement object detection and image classification - Process video and generate insights - Implement Azure AI Face service |
| Topic 3: Implement Natural Language Processing Solutions | 20-25% | - Analyze text using Azure AI Language - Create conversational AI solutions with Azure AI Bot Service - Build question answering solutions - Implement speech capabilities using Azure AI Speech - Translate text and speech |
| Topic 4: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement semantic and vector search - Create custom skills for Azure AI Search - Design document processing pipelines - Implement Azure AI Search solutions |
| Topic 5: Implement Decision Support Solutions | 10-15% | - Design and implement decision automation - Monitor and optimize decision support solutions - Integrate Azure AI services into applications |
| Topic 6: Implement Generative AI Solutions | 10-15% | - Use Azure OpenAI Service for generative AI - Apply responsible AI practices - Integrate Azure OpenAI models into applications - Implement prompt engineering techniques |
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NEW QUESTION # 98
You are building a chatbot by using the Microsoft Bot Framework Composer.
You have the dialog design shown in the following exhibit.
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:
Reference:
https://docs.microsoft.com/en-us/composer/concept-language-generation
https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/coalescefunction
NEW QUESTION # 99
You develop a custom question answering project in Azure AI Language. The project will be used by a chatbot.
You need to configure the project to engage in multi-turn conversations.
What should you do?
Answer: C
Explanation:
https://learn.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/multi-turn
NEW QUESTION # 100
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 are building a chatbot that will use question answering in Azure Cognitive Service for Language.
You have a PDF named Doc1.pdf that contains a product catalogue and a price list You upload Doc1.pdf and train the model.
During testing, users report that the chatbot responds correctly to the following question: What is the price of <product>?
The chatbot fails to respond to the following question: How much does < product > cost?
You need to ensure that the chatbot responds correctly to both questions.
Solution: From Language Studio, you add alternative phrasing to the question and answer pair, and then retrain and republish the model.
Does this meet the goal?
Answer: A
NEW QUESTION # 101
You have a chatbot that uses a QnA Maker application.
You enable active learning for the knowledge base used by the QnA Maker application.
You need to integrate user input into 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
Graphical user interface, application Description automatically generated
Step 1: For the knowledge base, select Show active learning suggestions.
In order to see the suggested questions, on the Edit knowledge base page, select View Options, then select Show active learning suggestions.
Step 2: Approve and reject suggestions.
Each QnA pair suggests the new question alternatives with a check mark, , to accept the question or an x to reject the suggestions. Select the check mark to add the question.
Step 3: Save and train the knowledge base.
Select Save and Train to save the changes to the knowledge base.
Step 4: Publish the knowledge base.
Select Publish to allow the changes to be available from the GenerateAnswer API.
When 5 or more similar queries are clustered, every 30 minutes, QnA Maker suggests the alternate questions for you to accept or reject.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/improve-knowledge-base
NEW QUESTION # 102
You are building a customer support chatbot.
You need to configure the bot to identify the following:
* Code names for internal product development
* Messages that include credit card numbers
The solution must minimize development effort.
Which Azure Cognitive Service for Language feature should you use for each requirement? To answer, drag the appropriate features to the correct requirements. Each feature may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 103
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