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| Section | Objectives |
|---|---|
| Implement Generative AI Solutions | - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions |
| Plan and Manage an Azure AI Solution | - Manage security, compliance, and responsible AI - Plan solution requirements and architecture - Select appropriate Azure AI services |
| Implement Computer Vision Solutions | - Implement custom vision models - Extract information using OCR and form recognition - Analyze images and videos using Azure AI Vision |
| Implement Natural Language Processing Solutions | - Translate and interpret language using Azure AI services - Analyze text using Azure AI Language - Implement question answering and conversational AI |
| Implement Knowledge Mining and Document Intelligence | - Enrich and index data for search scenarios - Implement document intelligence solutions - Build Azure AI Search solutions |
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NEW QUESTION # 305
You are building a multilingual chatbot.
You need to send a different answer for positive and negative messages.
Which two Text Analytics APIs should you use? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.
Answer: A,D
Explanation:
B: The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level.
D: The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
This capability is useful for content stores that collect arbitrary text, where language is unknown.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics- how-to-sentiment-analysis?tabs=version-3-1
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics- how-to-language-detection
NEW QUESTION # 306
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
a tabular form of rows and columns
* Relational data is, by definition, data that adheres to the relational model.
* In the relational model, data is organized into tables, which consist of rows (records or tuples) and columns (fields or attributes). This is known as the tabular form.
* The other options are incorrect:
* Unstructured data is the opposite of relational data.
* A hierarchical folder structure is used for file organization, not the logical structure of relational data.
* Comma-separated value (CSV) files can contain relational data, but the core definition of relational data is the tabular structure, not the file format itself.
Rationale
NEW QUESTION # 307
You need to upload speech samples to a Speech Studio project. How should you upload the samples?
Answer: D
Explanation:
When working with Speech Studio in Azure AI Speech (for example, to build a custom speech model for recognition or training purposes), you must provide speech samples along with their transcripts.
Requirements for Uploading Speech Samples:
Audio File Format
The supported format is .wav (PCM, 16-bit, 16 kHz or 8 kHz mono).
Other formats like .wma , .flac , or .mp3 are not accepted for training custom models.
Batch Upload via .zip
Audio files must be placed in a .zip archive.
The .zip file must also include a transcription file (usually a .txt or .json file) that maps the spoken audio in each .wav file to the correct text.
Transcript Format
Transcripts must be plain text, not Microsoft Word documents.
The transcript must align correctly with each audio file to ensure the Speech service learns from accurate mappings.
Option Analysis
A). Combine into one .wma file
Incorrect. .wma is not supported. Also, Speech Studio expects multiple .wav samples, not one big file.
B). Upload a .zip file containing .wav files + transcript
Correct. This is the officially supported method for uploading training data into a Speech Studio project.
C). Upload .flac files with Word transcript
Incorrect. .flac is not supported. Transcripts must be plain text, not Word files.
D). Upload individual .wma files
Incorrect. .wma is not supported.
The Answer: B. Upload a .zip file that contains a collection of audio files in the .wav format and a corresponding text transcript file.
Microsoft References
Prepare training data for Custom Speech
Speech Studio - Data Requirements
NEW QUESTION # 308
You are reviewing the design of a chatbot. The chatbot includes a language generation file that contains the following fragment.
# Greet(user)
- ${Greeting()}, ${user.name}
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: No
Example: Greet a user whose name is stored in `user.name`
- ${ welcomeUser(user.name) }
Example: Greet a user whose name you don't know:
- ${ welcomeUser() }
Box 2: No
Greet(User) is a Send a response action.
Box 3: Yes
Reference:
https://docs.microsoft.com/en-us/composer/how-to-ask-for-user-input
NEW QUESTION # 309
You plan to provision a QnA Maker service in a new resource group named RG1.
In RG1, you create an App Service plan named AP1.
Which two Azure resources are automatically created in RG1 when you provision the QnA Maker service? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,E
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/set-up-qnamaker-service-azure?tabs=v1#delete-azure-resources
"When you create a QnAMaker resource, you host the data in your own Azure subscription. Azure Search is used to index your data." & "When you create a QnAMaker resource, you host the runtime in your own Azure subscription. App Service is the compute engine that runs the QnA Maker queries for you."
Topic 1, Contoso, Ltd.
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
NEW QUESTION # 310
......
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