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| Section | Weight | Objectives |
|---|---|---|
| Plan and Manage an Azure AI Solution | 15-20% | - Manage AI costs and resource allocation - Select appropriate Azure AI services and technologies - Implement governance and compliance for AI solutions - Plan and configure secure AI solutions |
| Implement Generative AI Solutions | 10-15% | - Implement prompt engineering techniques - Apply responsible AI practices - Use Azure OpenAI Service for generative AI - Integrate Azure OpenAI models into applications |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement semantic and vector search - Create custom skills for Azure AI Search - Implement Azure AI Search solutions - Design document processing pipelines |
| Implement Computer Vision Solutions | 15-20% | - Analyze images using Azure AI Vision - Process video and generate insights - Implement object detection and image classification - Read and process documents using Azure AI Document Intelligence - Implement Azure AI Face service |
| Implement Decision Support Solutions | 10-15% | - Integrate Azure AI services into applications - Design and implement decision automation - Monitor and optimize decision support solutions |
| Implement Natural Language Processing Solutions | 20-25% | - Build question answering solutions - Create conversational AI solutions with Azure AI Bot Service - Implement speech capabilities using Azure AI Speech - Translate text and speech - Analyze text using Azure AI Language |
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問題 #305
You are building a Language Understanding solution.
You discover that many intents have similar utterances containing airport names or airport codes.
You need to minimize the number of utterances used to fram the model.
Which type of custom entity should you use?
答案：D
解題說明：
When many utterances differ only by airport names or codes, you don't want to list them all.
A Pattern.any entity acts as a placeholder for free-form input inside patterns, allowing the model to accept any word/phrase in that slot.
Machine-learning entities require lots of labeled utterances.
List entities work for fixed sets (e.g., specific known airport codes), but this scenario implies dynamic airport data.
Regex entities are for structured formats (like postal codes).
問題 #306
You are developing a photo application that will find photos of a person based on a sample image by using the Face API.
You need to create a POST request to find the photos.
How should you complete the 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.
答案：
解題說明：
Explanation
Box 1: findsimilars
https://docs.microsoft.com/en-us/rest/api/faceapi/face/find-similar
Box 2: matchPerson
Find similar has two working modes, "matchPerson" and "matchFace". "matchPerson" is the default mode that it tries to find faces of the same person as possible by using internal same-person thresholds. It is useful to find a known person's other photos. Note that an empty list will be returned if no faces pass the internal thresholds.
"matchFace" mode ignores same-person thresholds and returns ranked similar faces anyway, even the similarity is low. It can be used in the cases like searching celebrity-looking faces.
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/detectwithurl
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar
問題 #307
You are building a bot and that will use Language Understanding.
You have a LUDown file that contains the following content.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
答案：
解題說明：
Explanation:
Reference:
https://github.com/solliancenet/tech-immersion-data-ai/blob/master/ai-exp1/README.md
問題 #308
You have the following C# function.
You call the function by using the following code.
Following 'key phrases' what output will you receive?
答案：B
問題 #309
Drag and Drop Question
You are building a retail chatbot that will use a QnA Maker service.
You upload an internal support document to train the model. The document contains the following question: "What is your warranty period?" Users report that the chatbot returns the default QnA Maker answer when they ask the following question: "How long is the warranty coverage?" The chatbot returns the correct answer when the users ask the following question: 'What is your warranty period?" Both questions should return the same answer.
You need to increase the accuracy of the chatbot responses.
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.)
答案：
解題說明：
Explanation:
Step 1: Add alternative phrasing to the question and answer (QnA) pair. Add alternate questions to an existing QnA pair to improve the likelihood of a match to a user query.
Step 2: Retrain the model.
Periodically select Save and train after making edits to avoid losing changes.
Step 3: Republish the model
Note: A knowledge base consists of question and answer (QnA) pairs. Each pair has one answer and a pair contains all the information associated with that answer.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/edit-knowledge-base
問題 #310
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P.S. Testpdf在Google Drive上分享了免費的2026 Microsoft AI-102考試題庫：https://drive.google.com/open?id=1GOEDSOmjG0BW6fr8p5-5Tdcwlm70yUnn