최근 IT 업종에 종사하는 분들이 점점 늘어가는 추세하에 경쟁이 점점 치열해지고 있습니다. IT인증시험은 국제에서 인정받는 효력있는 자격증을 취득하는 과정으로서 널리 알려져 있습니다. Pass4Test의 Microsoft인증 AI-901덤프는IT인증시험의 한 과목인 Microsoft인증 AI-901시험에 대비하여 만들어진 시험전 공부자료인데 높은 시험적중율과 친근한 가격으로 많은 사랑을 받고 있습니다.
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Exam Price: | Approx. 99 USD (varies by region) |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Exam Duration: | 60 minutes |
| Related Certifications: | Microsoft Azure Data Fundamentals (DP-900) Microsoft Azure Fundamentals (AZ-900) |
| Passing Score: | 700 (out of 1000) |
| Exam Format: | Multiple choice, Case study (limited), Drag and drop, Multiple response |
| Available Languages: | German, Korean, Chinese (Traditional), Spanish, English, Japanese, Portuguese (Brazil), Chinese (Simplified), French |
| Real Exam Qty: | 40-60 |
| Recommended Training: | Microsoft Learn - AI-900 Learning Path Azure AI Fundamentals Course |
| Exam Registration: | Schedule exam via Pearson VUE Microsoft Certification Portal |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online proctored exam or in-person test center |
| Pre Condition: | No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
Microsoft AI-901인증덤프는 최근 출제된 실제시험문제를 바탕으로 만들어진 공부자료입니다. Microsoft AI-901 시험문제가 변경되면 제일 빠른 시일내에 덤프를 업데이트하여 최신버전 덤프자료를Microsoft AI-901덤프를 구매한 분들께 보내드립니다. 시험탈락시 덤프비용 전액환불을 약속해드리기에 안심하시고 구매하셔도 됩니다.
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질문 # 108
You are developing an application that analyzes voicemail recordings by using Azure Content Understanding in Foundry Tools.
You need to extract a transcript and structured information from the recordings.
Which type of analyzer should you use?
정답：D
설명：
To extract a transcript and structured information from voicemail recordings, you should use an audio analyzer.In Azure Content Understanding, analyzers are configured based on the type of data being processed. Since voicemail recordings are conversational audio content, an audio analyzer is designed to handle speech-to-text transcription, speaker labeling, and extracting the relevant structured fields.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/audio/overview
질문 # 109
Your company processes customer support emails.
You need to implement an AI solution that automatically identifies mentions of people, organizations, and locations in the emails.
Which text analysis technique should you use?
정답：B
설명：
The correct text analysis technique is Named Entity Recognition (NER).
Microsoft defines NER as a feature that identifies and categorizes entities in unstructured text, including people, places, and organizations.
Sentiment analysis detects positive, negative, or neutral opinion. Summarization creates shorter versions of text. Key phrase extraction identifies important phrases, but it does not specifically classify mentions as people, organizations, or locations.
질문 # 110
You have a Microsoft Foundry project that contains a vision-enabled model deployment. You need to create a prompt that ensures the model produces a relevant and useful response. What should you include in the prompt?
정답：D
설명：
To ensure a vision-enabled model produces a relevant and useful response, the prompt should include a clear description of the task . For example, you should tell the model what to do with the image, such as describe it, identify objects, compare images, extract visible text, or answer a specific question about the visual content.
The other options are incorrect:
B). a dataset ID for the image is not needed in the prompt.
C). the version number of the model is deployment/configuration information, not prompt content.
D). the deployment name of the model is used in the API call to route the request, not inside the prompt.
질문 # 111
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
정답：
설명：
질문 # 112
You have a dataset that contains experimental data for fuel samples.
You need to predict the amount of energy in kilojoules that can be obtained from a sample based on its measured density.
Which type of AI workload should you use?
정답：D
설명：
Regression is a supervised machine learning technique which is used to predict continuous values. The ultimate goal of the regression algorithm is to plot a best-fit line or a curve between the data. The three main metrics that are used for evaluating the trained regression model are variance, bias and error.
Reference:
https://builtin.com/data-science/regression-machine-learning
질문 # 113
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AI-901최신시험: https://www.pass4test.net/AI-901.html