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We provide updated and real Microsoft AI-102 exam questions that are sufficient to clear the Designing and Implementing a Microsoft Azure AI Solution (AI-102) exam in one go. The product of Prep4SureReview is created by seasoned professionals and is frequently updated to reflect changes in the content of the AI-102 Exam Questions.
To pass the exam, candidates must demonstrate their ability to design and implement AI solutions that meet specific business requirements. They must also be proficient in using Azure services to build intelligent applications that can process natural language, recognize images and speech, and make predictions based on data. Additionally, they must have a clear understanding of how to train and evaluate machine learning models, and how to deploy these models in production environments.
The AI-102 Exam is intended for professionals who are responsible for designing and implementing AI solutions that use Azure services. AI-102 exam is ideal for developers, architects, and data scientists who are interested in expanding their AI skills and knowledge. AI-102 exam covers a variety of topics, including designing AI solutions, implementing AI workflows, creating and deploying machine learning models, and integrating AI solutions with other Azure services.
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Microsoft AI-102 (Designing and Implementing a Microsoft Azure AI Solution) is a certification exam that aims to test candidates' knowledge and skills in designing and implementing AI solutions using Microsoft Azure. Designing and Implementing a Microsoft Azure AI Solution certification is intended for professionals who have experience working with Microsoft Azure and are looking to enhance their expertise in AI technologies. Successful completion of this certification exam can lead to career advancement opportunities and recognition as an expert in the field of AI.
NEW QUESTION # 60
You are developing an application that will use the Computer Vision client library. The application has the following code.
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:
Reference:
https://docs.microsoft.com/en-us/java/api/com.microsoft.azure.cognitiveservices.vision.computervision.computervision.analyzeimageinstreamasync
NEW QUESTION # 61
You have a chatbot that uses Azure OpenAI to generate responses.
You need to upload company data by using Chat playground. The solution must ensure that the chatbot uses the data to answer user questions.
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:
To make a chatbot use uploaded company data from the Chat playground ("use your data"), your code must:
* Create a chat request (not a plain completion), so you need the ChatCompletionsOptions type for the request options.
* This is the options class used for chat completions across Azure OpenAI SDKs and is the one that supports attaching data sources (extensions).
* Configure the Azure AI Search data source as a chat extension so the model grounds answers on your indexed documents.
* In the SDK, this is done by adding an AzureCognitiveSearchChatExtensionConfiguration entry under the extensions/dataSources collection and setting properties like SearchKey and IndexName. This is the specific configuration object for Azure AI Search integration with Chat Completions.
Therefore, the two dropdowns should be completed as:
* First dropdown: ChatCompletionsOptions()
* Second dropdown: AzureCognitiveSearchChatExtensionConfiguration
This matches how "Use your data (RAG)" is implemented in Azure OpenAI-chat request + Azure AI Search chat extension-so the bot can answer questions using your uploaded/company data. Microsoft Learn Microsoft Azure AI Solution References
* Azure OpenAI "Use your data" (concepts): how chat uses data sources like Azure AI Search. Microsoft Learn
* Azure OpenAI client library for .NET (overview of chat options and extensions support). Microsoft Learn
* Chat Completions Options (SDK docs, shows dataSources/extensions concept in chat options).
* Examples/discussion of AzureCognitiveSearchChatExtensionConfiguration usage with SearchKey
/IndexName.
NEW QUESTION # 62
You need to create a new resource that will be used to perform sentiment analysis and optical character recognition (OCR). The solution must meet the following requirements:
Use a single key and endpoint to access multiple services.
Consolidate billing for future services that you might use.
Support the use of Computer Vision in the future.
How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: PUT
Sample Request: PUT
https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/test-rg/ Reference:
https://docs.microsoft.com/en-us/rest/api/deviceupdate/resourcemanager/accounts/create
https://www.analyticsvidhya.com/blog/2020/12/microsoft-azure-cognitive-services-api-for-ai-development/
NEW QUESTION # 63
You have data saved in the following format.
Which format was used?
Answer: B
NEW QUESTION # 64
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? To answer, drag the appropriate values to the correct targets. Each value 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.
Answer:
Explanation:
Explanation
Box 1: LargeFaceListID
LargeFaceList: Add a face to a specified large face list, up to 1,000,000 faces.
Note: Given query face's faceId, to search the similar-looking faces from a faceId array, a face list or a large face list. A "faceListId" is created by FaceList - Create containing persistedFaceIds that will not expire. And a
"largeFaceListId" is created by LargeFaceList - Create containing persistedFaceIds that will also not expire.
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar
NEW QUESTION # 65
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