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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and manage an Azure AI solution | 20-25% | - Create and configure Azure AI resources - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Select appropriate Microsoft Foundry Services - Plan solutions aligned with responsible AI principles - Select suitable AI models |
| Topic 2: 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 3: 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 |
| Topic 4: Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Implement intelligent search and retrieval - Ingest and process structured/unstructured data |
| Topic 5: Implement generative AI solutions | 15-20% | - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Deploy and manage generative models - Integrate Azure OpenAI and other generative models - Implement model monitoring and feedback |
| Topic 6: Implement natural language processing solutions | 15-20% | - Customize and deploy NLP models - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots |
>> AI-102 Reliable Test Forum <<
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NEW QUESTION # 166
You have an Azure subscription that contains an Azure Al Document Intelligence resource named Aldoc1 in the SO tier.
You have the lies shown in the following table.
You need to train a custom extraction model by using AIdoc1.
Which files can you upload to Document Intelligence Studio?
Answer: C
NEW QUESTION # 167
You have an Azure subscription that has the following configurations:
* Subscription ID: 8d3591aa-96b8-4737-ad09-OOf9b1ed35ad
* Tenant ID: 3edfe572-cbS4-3ced-ae12-c5c177f39a12
You plan to create a resource that will perform sentiment analysis and optical character recognition (OCR).
You need to use an HTTP request to create the resource in the subscription. The solution must use a single key and endpoint.
How should you complete the request? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 168
You are building a retail chatbot that will use a QnA Maker service.
You upload an internal support document to train the model. The document contains the following question:
"What is your warranty period?"
Users report that the chatbot returns the default QnA Maker answer when they ask the following question:
"How long is the warranty coverage?"
The chatbot returns the correct answer when the users ask the following question: 'What is your warranty period?" Both questions should return the same answer.
You need to increase the accuracy of the chatbot responses.
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. (Choose three.)
Answer:
Explanation:
Explanation:
Step 1: Add alternative phrasing to the question and answer (QnA) pair.
Add alternate questions to an existing QnA pair to improve the likelihood of a match to a user query.
Step 2: Retrain the model.
Periodically select Save and train after making edits to avoid losing changes.
Step 3: Republish the model
Note: A knowledge base consists of question and answer (QnA) pairs. Each pair has one answer and a pair contains all the information associated with that answer.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/edit-knowledge-base
NEW QUESTION # 169
You have a chatbot that was built by using the Microsoft Bot Framework. You need to debug the chatbot endpoint remotely.
Which two tools should you install on a local computer? Each correct answer presents part of the solution.
(Choose two.)
NOTE: Each correct selection is worth one point.
Answer: B,C
Explanation:
When you want to debug a chatbot endpoint remotely that was built using the Microsoft Bot Framework, you need tools that allow you to test and tunnel your bot service to your local development environment.
* This is the official testing and debugging tool for bots built with the Microsoft Bot Framework.
* It allows developers to:
* Connect to a bot running locally or remotely.
* Inspect messages sent and received.
* Debug conversations and payloads in detail.
* Required for local testing of the bot.
* Correct.
* Ngrok is a tunneling tool that exposes your local development server (localhost) to the internet via a secure tunnel.
* This is essential when debugging remotely because the Bot Framework Service (Azure Bot Service) requires a publicly accessible HTTPS endpoint for communication.
* With ngrok, your local bot endpoint (e.g., http://localhost:3978/api/messages ) is mapped to a secure public endpoint (e.g., https://randomstring.ngrok.io/api/messages ).
* Correct.
1. Bot Framework Emulator 2. ngrok
* A. Fiddler
* A web debugging proxy. Useful for monitoring traffic, but not required for Bot Framework remote debugging.
* Incorrect.
* B. Bot Framework Composer
* A tool for building conversational bots visually. Not required for debugging an existing endpoint.
* Incorrect.
* D. Bot Framework CLI
* Used for bot project management and configuration. Not specifically required for remote debugging endpoints.
* Incorrect.
* F. nginx
* A web server/reverse proxy. Not needed for this scenario.
* Incorrect.
Incorrect Options
C). Bot Framework Emulator, E. ngrok
* Debug a bot locally using Bot Framework Emulator
* Use ngrok with Bot Framework Emulator
Microsoft References
NEW QUESTION # 170
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: B,C
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 # 171
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