Microsoft AI-102 Exam Preview | AI-102 Advanced Testing Engine

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Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Plan and Manage an Azure AI Solution15-20%- Manage AI costs and resource allocation
- Implement governance and compliance for AI solutions
- Plan and configure secure AI solutions
- Select appropriate Azure AI services and technologies
Implement Decision Support Solutions10-15%- Integrate Azure AI services into applications
- Monitor and optimize decision support solutions
- Design and implement decision automation
Implement Generative AI Solutions10-15%- Integrate Azure OpenAI models into applications
- Use Azure OpenAI Service for generative AI
- Implement prompt engineering techniques
- Apply responsible AI practices
Implement Knowledge Mining and Document Intelligence Solutions15-20%- Create custom skills for Azure AI Search
- Implement Azure AI Search solutions
- Design document processing pipelines
- Implement semantic and vector search
Implement Computer Vision Solutions15-20%- Implement Azure AI Face service
- Analyze images using Azure AI Vision
- Implement object detection and image classification
- Process video and generate insights
- Read and process documents using Azure AI Document Intelligence
Implement Natural Language Processing Solutions20-25%- Analyze text using Azure AI Language
- Build question answering solutions
- Implement speech capabilities using Azure AI Speech
- Translate text and speech
- Create conversational AI solutions with Azure AI Bot Service

>> Microsoft AI-102 Exam Preview <<

Microsoft AI-102 Advanced Testing Engine | AI-102 Latest Test Report

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Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q379-Q384):

NEW QUESTION # 379
You have a custom analyzer named analyzer1 that performs the following functions
* The transcription of video content
* The extraction of key frames from videos
You run the following command.

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:
The POST request starts an asynchronous analysis job for video01.mp4. Yes You use the URL in the Operation-Location header to poll and retrieve the results . Yes The POST does not return the full transcript/key frames in the response body (only 202 Accepted). No When you invoke a custom analyzer in Azure AI Content Understanding using the analyzers/{analyzerId} endpoint with API version 2024-12-01-preview , the service runs as a long-running operation. The initial response is 202 Accepted and includes an Operation-Location header pointing to the results URL. You then GET that URL to check status and, once complete, obtain outputs (for a video analyzer, this includes transcription and key frames because those capabilities are part of the analyzer definition). The header Ocp- Apim-Subscription-Key is valid for this API.
Microsoft References
* Quickstart (REST): asynchronous analyze call returns 202 with Operation-Location ; poll to get results.
Microsoft Learn
* What's new: API version 2024-12-01-preview . Microsoft Learn
* Prebuilt video analyzer functions (transcript + key frames). Custom analyzers inherit configured tasks.
Microsoft Learn
* REST API surface: Get Result and related operations for analyzers. Microsoft Learn
* Security header definition ( Ocp-Apim-Subscription-Key ). Microsoft Learn


NEW QUESTION # 380
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it as a result, these questions will not appear in the review screen.
You are building a chatbot that will use question answering in Azure Cognitive Service for Language.
You upload Doc1.pdf and train that contains a product catalogue and a price list.
During testing, users report that the chatbot responds correctly to the following question: What is the price of
<product>?
The chatbot fails to respond to the following question: How much does <product> cost?
You need to ensure that the chatbot responds correctly to both questions.
Solution: from Language Studio, you create an entity for price, and then retrain and republish the model.
Does this meet the goal?

Answer: B

Explanation:
Creating an entity for price is a feature of Conversational Language Understanding (CLU/LUIS), not Question Answering. Custom question answering does not use entities for extraction or intent resolution; it matches user utterances to Q/A pairs using alternates, synonyms, and ranking. Therefore, defining an "entity for price" would not make the chatbot correctly answer "How much does <product> cost?". The correct fix is to author additional alternate phrasings (as in Q266).
References
* Custom question answering capabilities (no entity modeling).https://learn.microsoft.com/azure/ai- services/language-service/question-answering/overview
* CLU entities vs. QnA authoring-separate features and workflows.https://learn.microsoft.com/azure/ai- services/language-service/conversational-language-understanding/overview


NEW QUESTION # 381
You have a bot that was built by using the Microsoft Bot Framework composer as shown in the following exhibit.

Use the drop-down menus 10 select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation


NEW QUESTION # 382
You are building a model to detect objects in images.
The performance of the model based on training data is shown in the following exhibit.

Answer:

Explanation:


NEW QUESTION # 383
You need to develop an extract solution for the receipt images. The solution must meet the document processing requirements and the technical requirements.
You upload the receipt images to the From Recognizer API for analysis, and the API returns the following JSON.

Which expression should you use to trigger a manual review of the extracted information by a member of the Consultant-Bookkeeper group?

Answer: C

Explanation:
Need to specify the field name, and then use < 0.7 to handle trigger if confidence score is less than 70%.
Reference:
https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/api-v2-0/reference-sdk-api-v2-0


NEW QUESTION # 384
......

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