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| Section | Weight | Objectives |
|---|---|---|
| Implement Generative AI Solutions | 10-15% | - Integrate Azure OpenAI models into applications - Use Azure OpenAI Service for generative AI - Apply responsible AI practices - Implement prompt engineering techniques |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement Azure AI Search solutions - Implement semantic and vector search - Design document processing pipelines - Create custom skills for Azure AI Search |
| Implement Natural Language Processing Solutions | 20-25% | - Analyze text using Azure AI Language - Translate text and speech - Implement speech capabilities using Azure AI Speech - Build question answering solutions - Create conversational AI solutions with Azure AI Bot Service |
| Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Integrate Azure AI services into applications - Design and implement decision automation |
| Implement Computer Vision Solutions | 15-20% | - Implement object detection and image classification - Process video and generate insights - Read and process documents using Azure AI Document Intelligence - Analyze images using Azure AI Vision - Implement Azure AI Face service |
| Plan and Manage an Azure AI Solution | 15-20% | - Implement governance and compliance for AI solutions - Plan and configure secure AI solutions - Select appropriate Azure AI services and technologies - Manage AI costs and resource allocation |
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NEW QUESTION # 361
Case Study 2 - Contoso, Ltd.
General Overview
Contoso, Ltd. is an international accounting company that has offices in France. Portugal, and the United Kingdom. Contoso has a professional services department that contains the roles shown in the following table.
Infrastructure
Contoso has the following subscriptions:
- Azure
- Microsoft 365
- Microsoft Dynamics 365
Azure Active (Azure AD) Directory
Contoso has Azure Active Directory groups for securing role-based access. The company uses the following group naming conventions:
- ICountryJ-[Levell-[Role]
- [Level]-[Role]
Intellectual Property
Contoso has the intellectual property shown in the following table.
Text-based content is provided only in one language and is not translated.
Planned Projects
Contoso plans to develop the following:
- A document processing workflow to extract information automatically from PDFs and images of financial documents
- A customer-support chatbot that will answer questions by using FAQs
- A searchable knowledgebase of all the intellectual property
Technical Requirements
Contoso identifies the following technical requirements:
- All content must be approved before being published.
- All planned projects must support English, French, and Portuguese.
- All content must be secured by using role-based access control (RBAC).
- RBAC role assignments must use the principle of least privilege.
- RBAC roles must be assigned only to Azure Active Directory groups.
- Al solution responses must have a confidence score that is equal to or greater than 70 percent.
- When the response confidence score of an Al response is lower than 70 percent, the response must be improved by human input.
Chatbot Requirements
Contoso identifies the following requirements for the chatbot:
- Provide customers with answers to the FAQs.
- Ensure that the customers can chat to a customer service agent.
- Ensure that the members of a group named Management-Accountants can approve the FAQs.
- Ensure that the members of a group named Consultant-Accountants can create and amend the FAQs.
- Ensure that the members of a group named the Agent-CustomerServices can browse the FAQs.
- Ensure that access to the customer service agents is managed by using Omnichannel for Customer Service.
- When the response confidence score is low.
- Ensure that the chatbot can provide other response options to the customers.
Document Processing Requirements
Contoso identifies the following requirements for document processing:
- The document processing solution must be able to process standardized financial documents that have the following characteristics:
- Contain fewer than 20 pages.
- Be formatted as PDF or JPEG files.
- Have a distinct standard for each office.
- The document processing solution must be able to extract tables and text from the financial documents.
- The document processing solution must be able to extract information from receipt images.
- Members of a group named Management-Bookkeeper must define how to extract tables from the financial documents.
- Members of a group named Consultant-Bookkeeper must be able to process the financial documents.
Knowledgebase Requirements
Contoso identifies the following requirements for the knowledgebase:
- Supports searches for equivalent terms
- Can transcribe jargon with high accuracy
- Can search content in different formats, including video
- Provides relevant links to external resources for further research
You are developing the document processing workflow.
You need to identify which API endpoints to use to extract text from the financial documents.
The solution must meet the document processing requirements.
Which two API endpoints should you identify? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: C,E
Explanation:
Query the status and retrieve the result of an Analyze Receipt operation.
Request URL:
https://{endpoint}/formrecognizer/v2.0-preview/prebuilt/receipt/analyzeResults/{resultId} POST {Endpoint}/vision/v3.2/read/analyze Use this interface to get the result of a Read operation, employing the state-of-the-art Optical Character Recognition (OCR) algorithms optimized for text-heavy documents.
Scenario: Contoso plans to develop a document processing workflow to extract information automatically from PDFs and images of financial documents The document processing solution must be able to process standardized financial documents that have the following characteristics:
- Contain fewer than 20 pages.
- Be formatted as PDF or JPEG files.
- Have a distinct standard for each office.
- The document processing solution must be able to extract tables and text from the financial documents.
- The document processing solution must be able to extract information from receipt images.
Reference:
https://westus2.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2- preview/operations/GetAnalyzeReceiptResult
https://docs.microsoft.com/en-us/rest/api/computervision/3.1/read/read
NEW QUESTION # 362
You are building an app that will analyze text by using the Azure Al Language service.
You need to configure the app to mask the telephone number and email details in a given document.
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:
NEW QUESTION # 363
You are building an app that will process incoming email and direct email messages to either French or English language support teams.
Which Azure Cognitive Services API should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The task is to process incoming emails and route them to French or English support teams. This means we need to detect the language of each email.
Let's break it down:
Which Cognitive Service is needed?
Azure Text Analytics (part of Azure AI Language) provides a Language Detection API.
The Translator service is used for translation, not just detecting the original language. Since the requirement is only to decide whether to send emails to French or English teams, we just need to detect the language.
Endpoint selection
Text Analytics uses regional endpoints such as:
https:// < region > .api.cognitive.microsoft.com/
For example: eastus.api.cognitive.microsoft.com is valid.
api.cognitivemicrosofttranslator.com # incorrect (this is for Translator service).
portal.azure.com # Azure portal, not an API endpoint.
API Path selection
To detect language, you call:
/text/analytics/v3.1/languages
/text/analytics/v3.1/entities/recognition/general # entity recognition, not language.
/translator/text/v3.0/... # translation, not language detection.
Correct Answer Combination:
eastus.api.cognitive.microsoft.com
/text/analytics/v3.1/languages
Microsoft References
Text Analytics Language Detection API
Text Analytics REST API v3.1
NEW QUESTION # 364
You train an Azure Custom Vision object detection model to identify a company's products by using the Retail domain.
You plan to deploy the model as part of a mobile app for Android phones.
You need to prepare the model for deployment.
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:
For deployment to a mobile app (Android), Custom Vision requires a compact domain so the model can be exported and run on-device (e.g., as TensorFlow Lite or ONNX). The model was trained using the Retail domain, which is not an exportable compact domain for object detection. Therefore:
* Change the model domain to an exportable Object Detection (compact) domain (e.g., General
[compact]).
* Retrain the model so weights are learned under the new domain-domain changes require retraining.
* Export the model for Android (typically TensorFlow Lite or ONNX) and integrate it into the app.
This sequence prepares the model for on-device mobile deployment with minimal extra development.
References (Microsoft Azure AI Solution)
* Custom Vision: Only compact domains support model export for edge/mobile.
* Changing a domain requires retraining the iteration.
* Exporting object detection models supports TensorFlow/TensorFlow Lite/ONNX formats for Android integration.
NEW QUESTION # 365
You are building a chatbot by using the Microsoft Bot Framework Composer as shown in the exhibit. (Click the Exhibit tab.)
The chatbot contains a dialog named GetUserDetails. GetUserDetails contains a TextInput control that prompts users for their name.
The user input will be stored in a property named name.
You need to ensure that you can dispose of the property when the last active dialog ends.
Which scope should you assign to name?
Answer: A
Explanation:
The dialog scope associates properties with the active dialog. Properties in the dialog scope are retained until the dialog ends.
Reference:
https://docs.microsoft.com/en-us/composer/concept-memory?tabs=v2x
NEW QUESTION # 366
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