PassTIP AI-102 최신 PDF 버전 시험 문제집을 무료로 Google Drive에서 다운로드하세요: https://drive.google.com/open?id=1PKSuXQ4gulnW8Ql3yTB3v1zpdON1BcPh
PassTIP 에서 제공해드리는 Microsoft AI-102덤프는 아주 우수한 IT인증덤프자료 사이트입니다. IT업계엘리트한 강사들이 퍼펙트한 Microsoft AI-102 덤프문제집을 제작하여 디테일한 시험문제와 답으로 여러분이 아주 간단히Microsoft AI-102시험을 패스할 수 있도록 최선을 다하고 있습니다.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement Computer Vision Solutions | 15-20% | - Read and process documents using Azure AI Document Intelligence - Analyze images using Azure AI Vision - Implement object detection and image classification - Process video and generate insights - Implement Azure AI Face service |
| Topic 2: Plan and Manage an Azure AI Solution | 15-20% | - Select appropriate Azure AI services and technologies - Implement governance and compliance for AI solutions - Manage AI costs and resource allocation - Plan and configure secure AI solutions |
| Topic 3: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement Azure AI Search solutions - Create custom skills for Azure AI Search - Design document processing pipelines - Implement semantic and vector search |
| Topic 4: Implement Generative AI Solutions | 10-15% | - Integrate Azure OpenAI models into applications - Use Azure OpenAI Service for generative AI - Implement prompt engineering techniques - Apply responsible AI practices |
| Topic 5: Implement Natural Language Processing Solutions | 20-25% | - Build question answering solutions - Implement speech capabilities using Azure AI Speech - Create conversational AI solutions with Azure AI Bot Service - Translate text and speech - Analyze text using Azure AI Language |
| Topic 6: Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Design and implement decision automation - Integrate Azure AI services into applications |
Microsoft업계에 종사하시는 분들은 AI-102인증시험을 통한 자격증취득의 중요성을 알고 계실것입니다. PassTIP에서 제공해드리는 인증시험대비 고품질 덤프자료는 제일 착한 가격으로 여러분께 다가갑니다. PassTIP덤프는 AI-102인증시험에 대비하여 제작된것으로서 높은 적중율을 자랑하고 있습니다.덤프를 구입하시면 일년무료 업데이트서비스, 시험불합격시 덤프비용환불 등 퍼펙트한 서비스도 받을수 있습니다.
질문 # 111
For each of the following statements, select Yes if the statement is tine. Otherwise, select No. NOTE: Each correct selection is worth one point.
정답：
설명：
Explanation:
질문 # 112
You are developing a method that uses the Computer Vision client library. The method will perform optical character recognition (OCR) in images. The method has the following code.
During testing, you discover that the call to the GetReadResultAsync method occurs before the read operation is complete.
You need to prevent the GetReadResultAsync method from proceeding until the read operation is complete.
Which two actions should you perform? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.
정답：A,C
설명：
The method shown uses the Read API of the Azure Computer Vision client library. The ReadAsync call submits the OCR job and returns an Operation-Location header, which contains the operationId. Then GetReadResultAsync(Guid.Parse(operationId)) is called to fetch the result.
* The Read API is asynchronous.
* Submitting the read request does not mean the OCR has finished.
* If you immediately call GetReadResultAsync, the operation may still be in progress, resulting in incomplete or empty results.
* Check the results.Status property
* The response from GetReadResultAsync includes a status property.
* Possible values: notStarted, running, succeeded, failed.
* You must wait until the status is succeeded before processing results.
* This ensures you don't attempt to read lines before OCR has completed.
* This corresponds to B.
* Wrap in a loop with delay
* Since OCR takes time, you need to poll the service until the status becomes succeeded or failed.
* A typical pattern is:
* ReadOperationResult results;
* do
* {
* results = await client.GetReadResultAsync(Guid.Parse(operationId));
* await Task.Delay(1000); // wait 1 second before retrying
* }
* while (results.Status == OperationStatusCodes.Running || results.Status == OperationStatusCodes.
NotStarted);
* This corresponds to D.
* A. Remove the Guid.Parse(operationId) parameter
* Incorrect. The operationId is required to fetch the OCR results.
* B. Add code to verify the results.Status value
* Correct. You must check whether the operation has completed.
* C. Add code to verify the status of the txtHeaders.Status value
* Incorrect. txtHeaders only contains metadata and the operation location. The OCR completion status comes from the results.Status in the GetReadResultAsync response, not from txtHeaders.
* D. Wrap the call to GetReadResultAsync within a loop that contains a delay
* Correct. This is how you poll until the operation has finished.
The answer: B and D
* Azure Computer Vision Read API
* Read text using the Computer Vision client library
질문 # 113
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.)
정답：
설명：
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/edit-knowledge-base
질문 # 114
You are building a chatbot.
You need to use the Content Moderator API to identify aggressive and sexually explicit language.
Which three settings should you configure? To answer, select the appropriate settings in the answer area.
NOTE: Each correct selection is worth one point.
정답：
설명：
Explanation:
To detect aggressive language (e.g., profanity/abuse) and sexually explicit content in text using the Content Moderator Text - Screen API:
classify = true
Enables machine-assisted text classification that returns category scores (e.g., sexually explicit/suggestive categories). This is required to identify sexual content.
language = < code > (for example, eng )
Specifies the language so profanity/abusive terms are detected correctly. The profanity detection in Text- Screen is language dependent.
autocorrect = true
Helps normalize intentionally misspelled or obfuscated words so that profanity or aggressive terms are still detected (e.g., "f@#$" # "fuck").
Other parameters in the blade are not necessary for this goal:
PII targets personal data extraction, not aggression/sexuality.
listId is for matching against custom blocklists.
Headers like Ocp-Apim-Subscription-Key and Content-Type are required to call the API, but they are not the content-analysis settings that control detection behavior asked for in this question.
Microsoft Azure AI References
Azure AI Content Moderator - Screen text API parameters (autocorrect, language, classify) and category outputs.
Azure AI Content Moderator - Text moderation concepts: profanity detection and classification categories.
질문 # 115
Select the answer that correctly completes the sentence.
정답：
설명：
Explanation:
질문 # 116
......
PassTIP의 제품들은 모두 우리만의 거대한IT업계엘리트들로 이루어진 그룹 즉 관련업계예서 권위가 있는 전문가들이 자기만의 지식과 지금까지의 경험으로 최고의 IT인증관련자료를 만들어냅니다. PassTIP의 문제와 답은 정확도 적중률이 아주 높습니다. 우리의 덤프로 완벽한Microsoft인증AI-102시험대비를 하시면 되겠습니다. 이렇게 어려운 시험은 우리Microsoft인증AI-102덤프로 여러분의 고민과 꿈을 한방에 해결해드립니다.
AI-102최신 덤프샘플문제 다운: https://www.passtip.net/AI-102-pass-exam.html
참고: PassTIP에서 Google Drive로 공유하는 무료 2026 Microsoft AI-102 시험 문제집이 있습니다: https://drive.google.com/open?id=1PKSuXQ4gulnW8Ql3yTB3v1zpdON1BcPh