AI-901 Korean exam dumps

Microsoft AI-901 Korean Value Package

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  • Exam Code: AI-901 Korean
  • Exam Name: Microsoft Azure AI Fundamentals (AI-901 Korean Version)
  • No. of Questions: 132 Questions and Answers
  • Updated: Oct 19, 2026

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Microsoft AI-901 Korean Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals
Exam Number:AI-900
Passing Score:700 / 1000
Available Languages:Spanish, English, French, German, Indonesian (Indonesia), Japanese, Arabic (Saudi Arabia), Italian, Korean, Portuguese (Brazil), Chinese (Traditional), Chinese (Simplified), Russian
Real Exam Qty:40-60
Certificate Validity Period:1 year (renewable via free online assessment on Microsoft Learn)
Exam Format:Drag and drop, Scenario-based, Multiple choice, Match the service to use case, Multiple select
Exam Duration:45-60
Related Certifications:Microsoft Certified: Azure AI Fundamentals
Exam Price:USD 99
Sample Questions: DOWNLOAD DEMO
Exam Way:Online (remote proctored via Pearson VUE) or at a Pearson VUE test center
Pre Condition:No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900

Microsoft AI-901 Korean Exam Syllabus Topics:

SectionWeightObjectives
Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)15-20%- Identify features of common NLP workload scenarios
  • 1. Identify features and uses for translation
  • 2. Identify features and uses for key phrase extraction
  • 3. Identify features and uses for language modeling
  • 4. Identify features and uses for sentiment analysis
  • 5. Identify features and uses for speech recognition and synthesis
  • 6. Identify features and uses for entity recognition
- Identify Azure tools and services for NLP workloads
  • 1. Describe capabilities of the Azure AI Speech service
  • 2. Describe capabilities of the Azure AI Language service
Describe features of generative AI workloads on Azure (20-25%)20-25%- Identify features of generative AI solutions
  • 1. Identify common scenarios for generative AI
  • 2. Identify responsible AI considerations for generative AI
  • 3. Identify features of generative AI models
- Identify generative AI services and capabilities in Microsoft Azure
  • 1. Describe features and capabilities of Azure OpenAI service
  • 2. Describe features and capabilities of Azure AI Foundry
  • 3. Describe features and capabilities of Azure AI Foundry model catalog
Describe Artificial Intelligence workloads and considerations (15-20%)15-20%- Identify features of common AI workloads
  • 1. Identify features of Natural Language Processing (NLP) workloads
  • 2. Identify features of computer vision workloads
  • 3. Identify features of document intelligence workloads
  • 4. Identify features of generative AI workloads
  • 5. Identify features of knowledge mining workloads
  • 6. Identify features of content moderation and moderation workloads
- Identify guiding principles for responsible AI
  • 1. Describe considerations for transparency in an AI solution
  • 2. Describe considerations for inclusiveness in an AI solution
  • 3. Describe considerations for privacy and security in an AI solution
  • 4. Describe considerations for fairness in an AI solution
  • 5. Describe considerations for reliability and safety in an AI solution
  • 6. Describe considerations for accountability in an AI solution
Describe features of computer vision workloads on Azure (15-20%)15-20%- Identify Azure tools and services for computer vision tasks
  • 1. Describe capabilities of the Azure AI Face detection service
  • 2. Describe capabilities of the Azure AI Vision service
- Identify common types of computer vision solution
  • 1. Identify features of object detection solutions
  • 2. Identify features of image classification solutions
  • 3. Identify features of optical character recognition (OCR) solutions
  • 4. Identify features of image analysis solutions
  • 5. Identify features of face detection and identification solutions
  • 6. Identify features of semantic segmentation solutions
Describe fundamental principles of machine learning on Azure (15-20%)15-20%- Identify common machine learning techniques
  • 1. Identify regression machine learning scenarios
  • 2. Identify clustering machine learning scenarios
  • 3. Identify features of deep learning techniques
  • 4. Identify classification machine learning scenarios
- Describe Azure Machine Learning capabilities
  • 1. Describe data and compute services for data science and machine learning
  • 2. Describe model management and deployment capabilities in Azure Machine Learning
  • 3. Describe capabilities of automated machine learning
- Describe core machine learning concepts
  • 1. Identify features and labels for training data in machine learning
  • 2. Describe how training and validation datasets are used in machine learning

AI-901 Korean Exam FAQ: Details Every Candidate Should Know

The official outline groups the AI-901 Korean exam content into weighted domains, including:

  • Describe features of computer vision workloads on Azure (15-20%) (15-20%)
  • Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%) (15-20%)
  • Describe Artificial Intelligence workloads and considerations (15-20%) (15-20%)

The three versions of the Microsoft Azure AI Fundamentals (AI-901 Korean Version) materials at PrepAwayTest all follow this objective structure, so whichever format you study in, you are working on what the exam actually covers.

The AI-901 Korean exam contains 40-60 questions to be completed in 45-60 minutes. Simulating that exact pressure in advance is straightforward: the PC test engine version of the PrepAwayTest materials recreates the real exam environment, so timed practice feels like the genuine article.

Yes. Privacy is a stated commitment, not a footnote: your address, email, and other personal details are never revealed to any other person or institution while you purchase or use the Microsoft Azure AI Fundamentals (AI-901 Korean Version) materials. Payment is processed by Credit Card through a secure channel, adding a second layer of protection to the transaction. And if anything ever feels unclear, our service staff is reachable by email anytime and replies promptly.

No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial.

The AI-901 Korean exam is the official test behind the Microsoft Azure AI Fundamentals (AI-901 Korean Version) certification from Microsoft. It verifies that you can apply the published exam objectives in practical scenarios, and the credential signals to employers that your skills have been measured against an industry-recognized standard — useful whether you are an office worker aiming at promotion or a student building a foundation.

Three versions, designed for different study habits. The PDF version is easy to read and print, ideal for annotating on paper. The SOFT version is a PC test engine that simulates the real AI-901 Korean exam environment, helping you adapt to exam mode before the day arrives. The APP version is an online test engine that supports any electronic equipment — phone, tablet, or computer — so you can review on the subway or anywhere else. All three contain the same 132 practice questions for the AI-901 Korean exam with expert-verified answers.

You need 700 / 1000 to pass, and the exam fee is USD 99. Treating the fee as a one-time investment is a good mindset: steady timed practice until your scores sit comfortably above the passing line is far cheaper than a retake.

Microsoft Azure AI Fundamentals (AI-901 Korean Version) Sample Questions:

다음과 같은 REST API 요청이 있습니다.

이 요청을 처리하려면 어떤 Azure OpenAI 모델을 사용해야 할까요?

  • A. GPT-4.1
  • B. E에서
  • C. 코덱스
  • D. 속삭임
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).

생성형 AI 모델을 Microsoft Foundry 프로젝트에 배포하고 있습니다. 모델에 더 높은 분당 토큰 수(TPM)를 할당했습니다. 이 변경의 결과는 무엇입니까?

  • A. 해당 모델은 더 긴 응답을 생성합니다.
  • B. 이 모델은 더 간결한 답변과 더 많은 출처 인용을 생성합니다.
  • C. 모델의 Azure 지역 가용성이 변경됩니다.
  • D. 모델 배포가 입력값 변화를 처리할 수 있는 속도와 규모
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).

문장을 올바르게 완성하는 답을 고르시오.

Reveal Solution  Discussion  0

Correct Answer:


Explanation:
The correct answer is API endpoint. After a generative AI model is deployed in Microsoft Foundry, the deployment exposes an inference endpoint through which external applications can submit requests and receive generated responses. Microsoft Foundry documentation describes deployed models as being accessible programmatically through an endpoint and associated credentials. Applications invoke the relevant REST API or SDK against this endpoint and specify the deployed model as required by the API.
An embedding vector is a numerical representation of semantic information used for similarity search, retrieval, and grounding; it is not the network interface through which a deployed model is invoked. A training dataset contains data used to train or fine-tune a model and is not called when performing inference.
A URL parameter can be part of an API request, but it does not represent the deployed model ' s callable interface.
This directly aligns with the AI-901 objective to deploy a model and interact with it in the Foundry portal and to create lightweight applications that invoke deployed generative AI models through supported APIs and SDKs.

Microsoft Foundry에 멀티모달 모델이 배포되어 있습니다.
이미지를 분석하고 텍스트 요약과 오디오 요약을 모두 제공하도록 모델을 구성해야 합니다.
모델에게 보내야 하는 최소 사용자 프롬프트 수는 몇 개입니까?

  • A. 1
  • B. A
  • C. 2
  • D. 3
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).

귀사는 고객 지원 이메일을 처리합니다.
이메일에서 사람, 조직, 위치에 대한 언급을 자동으로 식별하는 AI 솔루션을 구현해야 합니다.
어떤 텍스트 분석 기법을 사용해야 할까요?

  • A. 개체명 인식(NER)
  • B. 핵심 문구 추출
  • C. 요약
  • D. 감정 분석
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Explanation: Only visible for PrepAwayTest members. You can sign-up / login (it's free).

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