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ActualtestPDF has one of the most comprehensive and top-notch Microsoft AI-102 Exam Questions. We eliminated the filler and simplified the Designing and Implementing a Microsoft Azure AI Solution preparation process so you can ace the Microsoft certification exam on your first try. Our Microsoft AI-102 Questions include real-world examples to help you learn the fundamentals of the subject not only for the Microsoft exam but also for your future job.
| Section | Objectives |
|---|---|
| Topic 1: Implement Knowledge Mining and Document Intelligence | - Build Azure AI Search solutions - Implement document intelligence solutions - Enrich and index data for search scenarios |
| Topic 2: Plan and Manage an Azure AI Solution | - Plan solution requirements and architecture - Select appropriate Azure AI services - Manage security, compliance, and responsible AI |
| Topic 3: Implement Generative AI Solutions | - Build retrieval-augmented generation (RAG) solutions - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions |
| Topic 4: Implement Natural Language Processing Solutions | - Analyze text using Azure AI Language - Implement question answering and conversational AI - Translate and interpret language using Azure AI services |
| Topic 5: Implement Computer Vision Solutions | - Analyze images and videos using Azure AI Vision - Implement custom vision models - Extract information using OCR and form recognition |
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NEW QUESTION # 106
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:
NEW QUESTION # 107
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Azure Synapse Analytics (formerly Azure SQL Data Warehouse) uses a massively parallel processing (MPP) architecture for big data and analytics workloads.
* Control Node:
* Acts as the brain of the system.
* Receives queries, optimizes them, and then coordinates execution.
* Does not perform large-scale data crunching itself.
* Compute Nodes:
* Perform the actual parallel execution of queries.
* Data is distributed across these nodes.
* The MPP engine breaks down queries into smaller tasks and distributes them to compute nodes for fast, parallel execution.
* Distributes processing across compute nodes # Correct. This is the essence of MPP.
* Distributes processing across control nodes # Incorrect. The control node does not process queries in parallel; it coordinates them.
* Redirects client connections across compute nodes # Incorrect. Client connections go to the control node, not directly to compute nodes.
* Redirects client connections across control nodes # Incorrect. There is typically one control node per Synapse instance.
Review of Answer Options:
The Answer: Distributes processing across compute nodes
* Azure Synapse Analytics architecture
* Distributed query processing in Azure Synapse
Microsoft References
NEW QUESTION # 108
You are developing a streaming Speech to Text solution that will use the Speech SDK and MP3 encoding.
You need to develop a method to convert speech to text for streaming MP3 data.
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:
Explanation:
Scenario Recap
You are building a streaming Speech-to-Text solution using the Speech SDK.
Input audio format: MP3 encoding
You must configure the audio stream format and the recognizer properly.
Code Analysis
Audio Format
For MP3 streams, the correct method is:
AudioStreamFormat.GetCompressedFormat(AudioStreamContainerFormat.MP3)
This creates an audio format object for compressed MP3 input.
Recognizer
Since the task is speech-to-text transcription, you need the SpeechRecognizer class.
Other options like KeywordRecognizer, SpeakerRecognizer, or SpeechSynthesizer are not appropriate (they handle keyword spotting, speaker identification, or text-to-speech).
Completed Code Snippet
var audioFormat = AudioStreamFormat.GetCompressedFormat(AudioStreamContainerFormat.MP3); var speechConfig = SpeechConfig.FromSubscription( " 18c51a87-3a69-47a8-aedc-a54745f708a1 " , " westus
" );
var audioConfig = AudioConfig.FromStreamInput(pushStream, audioFormat); using ( var recognizer = new SpeechRecognizer(speechConfig, audioConfig))
{
var result = await recognizer.RecognizeOnceAsync();
var text = result.Text;
}
Final Answer (Answer Area Selections)
AudioFormat: AudioStreamFormat.GetCompressedFormat
Recognizer: SpeechRecognizer
Microsoft References
Speech SDK - AudioStreamFormat
SpeechRecognizer class
NEW QUESTION # 109
You have an Azure subscription that contains an Azure OpenA1 resource named AH.
You plan to build an app named App1 that will write press releases by using AM.
You need to deploy an Azure OpenA1 model for Appl. The solution must minimize development effort.
Which three actions should you perform in sequence in Azure OpenAI Studio? 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:
The requirement:
* You have an Azure OpenAI resource.
* You want to build an app (App1) that writes press releases.
* The solution must minimize development effort.
Step 1 - Select the model deployment
* Since press release generation requires natural language generation, the best choice is GPT-3.5 Turbo.
* The text-embedding-ada-002 model is used for semantic search and embeddings, not text generation, so it's not appropriate here.
Step 2 - Apply a system message template
* Azure OpenAI Studio provides pre-built system message templates to speed up development.
* For writing press releases, the correct template is the Marketing Writing Assistant template.
* This minimizes development effort since it already configures prompt engineering for marketing copywriting.
Step 3 - Deploy the solution
* Once the deployment and template are configured, you deploy the solution to a new web app so it can be used as App1.
Correct Sequence:
* Create a deployment that uses the GPT-3.5 Turbo model.
* Apply the Marketing Writing Assistant system message template.
* Deploy the solution to a new web app.
* Azure OpenAI Studio - Getting Started
* Azure OpenAI GPT-3.5 models
* Azure OpenAI Studio system message templates
NEW QUESTION # 110
You are building an Azure Cognitive Search custom skill.
You have the following custom skill schema definition.
For each of the following statements, select Yes if the statement. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-output-field-mapping
Topic 1, Contoso, Ltd.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab. note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
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
NEW QUESTION # 111
......
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