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Um die AI-102-Zertifizierungsprüfung abzulegen, sollten die Kandidaten ein gutes Verständnis für Azure-Dienste, Erfahrung mit Datenwissenschaft und maschinellem Lernen sowie Kenntnisse über Programmiersprachen wie Python und R. Aufgaben, die die Fähigkeit des Kandidaten bewerten, KI -Lösungen auf Azure zu entwerfen und umzusetzen. Das Bestehen dieser Zertifizierungsprüfung zeigt, dass der Kandidat über die Fähigkeiten und Kenntnisse verfügt, die für die Gestaltung und Implementierung von KI -Lösungen mithilfe von Microsoft Azure erforderlich sind, was ihnen helfen kann, ihre Karriere im Bereich KI und maschinelles Lernen voranzutreiben.
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Die Microsoft AI-102-Prüfung, auch bekannt als "Designing and Implementing a Microsoft Azure AI Solution", ist eine Zertifizierungsprüfung, die sich auf die Prüfung der Fähigkeiten und Kenntnisse von Fachleuten konzentriert, die mit Microsoft Azure AI-Lösungen arbeiten. Diese Prüfung ist für Personen konzipiert, die Erfahrung in der Entwicklung und Bereitstellung von AI-Lösungen mit Azure Cognitive Services, Machine Learning und anderen Azure AI-Technologien haben.
Die Microsoft AI-102 Prüfung ist eine wesentliche Zertifizierung für Fachleute, die ihre Kompetenz im Entwurf und der Umsetzung von AI-Lösungen in Azure demonstrieren möchten. Es ist eine anspruchsvolle Prüfung, die von den Kandidaten ein tiefes Verständnis von AI-Konzepten und praktische Erfahrung in der Umsetzung von AI-Lösungen in Azure erfordert. Durch das Bestehen dieser Prüfung können Kandidaten ihre Kompetenz im Entwurf und der Umsetzung von AI-Lösungen in Azure demonstrieren und sich in dem hochkompetitiven Bereich der AI differenzieren.
289. Frage
You are using a Language Understanding service to handle natural language input from the users of a web-based customer agent.
The users report that the agent frequently responds with the following generic response: "Sorry, I don't understand that." You need to improve the ability of the agent to respond to requests.
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.)
Antwort:
Begründung:
290. Frage
You have an Azure subscription that contains an Azure OpenAI resource named AM.
You build a chatbot that uses All to provide generative answers to specific questions.
You need to ensure that questions intended to circumvent built-in safety features are blocked.
Which Azure Al Content Safety feature should you implement?
Antwort: D
291. Frage
You are developing the smart e-commerce project.
You need to design the skillset to include the contents of PDFs in searches.
How should you complete the skillset design diagram? To answer, drag the appropriate services to the correct stages. Each service 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.
Antwort:
Begründung:
Explanation
Box 1: Azure Blob storage
At the start of the pipeline, you have unstructured text or non-text content (such as images, scanned documents, or JPEG files). Data must exist in an Azure data storage service that can be accessed by an indexer.
Box 2: Computer Vision API
Scenario: Provide users with the ability to search insight gained from the images, manuals, and videos associated with the products.
The Computer Vision Read API is Azure's latest OCR technology (learn what's new) that extracts printed text (in several languages), handwritten text (English only), digits, and currency symbols from images and multi-page PDF documents.
Box 3: Translator API
Scenario: Product descriptions, transcripts, and all text must be available in English, Spanish, and Portuguese.
Box 4: Azure Files
Scenario: Store all raw insight data that was generated, so the data can be processed later.
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-concept-intro
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr
Topic 2, Contoso, Ltd.Case Study
This is a case study Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
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
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
292. Frage
You plan to use a Conversational Language Understanding application named app1 that is deployed to a container. App1 was developed by using a Conversational Language Understanding authoring resource named Iu1. App1 has the versions shown in the following table.
You need to create a container that uses the latest deployable version of app1.
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.
Antwort:
Begründung:
Explanation:
293. Frage
You develop an application that uses the Face API.
You need to add multiple images to a person group.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Antwort:
Begründung:
Explanation:
Comprehensive Detailed Explanation
You're adding multiple images for each person into a PersonGroup using the Face API SDK.
File.OpenRead(imagePath) returns a Stream, so the using declaration must declare Stream t = File.OpenRead (imagePath) .
To upload an image from a stream to a person in a person group, call
faceClient.PersonGroupPerson.AddFaceFromStreamAsync(personGroupId, personId, t); Putting it together:
Parallel.For( 0 , PersonCount, async i = >
{
Guid personId = persons[i].PersonId;
string personImageDir = $ " /path/to/person/ {i} /images " ;
foreach ( string imagePath in Directory.GetFiles(personImageDir, " *.jpg " ))
{
using (Stream t = File.OpenRead(imagePath))
{
await faceClient.PersonGroupPerson.AddFaceFromStreamAsync(
personGroupId, personId, t);
}
}
});
This loops the images for each person, opens each as a stream, and adds the face to the specified person in the person group.
References
Microsoft Docs - Face API: Add a face to a person ( AddFaceFromStreamAsync , AddFaceFromUrlAsync ) in PersonGroupPerson operations.
https://learn.microsoft.com/azure/ai-services/face/ (see SDK/PersonGroupPerson methods) NET File.OpenRead returns Stream .
https://learn.microsoft.com/dotnet/api/system.io.file.openread
294. Frage
......
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