Microsoft Azure AI Fundamentals (AI-901 Korean Version) : AI-901 Korean valid dump

AI-901 Korean
  • Exam Code: AI-901-KR
  • Exam Name: Microsoft Azure AI Fundamentals (AI-901 Korean Version)
  • Updated: Oct 18, 2026
  • Q & A: 132 Questions and Answers

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Microsoft AI-901 Korean Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals
Exam Number:AI-900
Real Exam Qty:40-60
Passing Score:700 / 1000
Certificate Validity Period:1 year (renewable via free online assessment on Microsoft Learn)
Available Languages:English, French, Portuguese (Brazil), Spanish, German, Italian, Arabic (Saudi Arabia), Japanese, Indonesian (Indonesia), Korean, Chinese (Simplified), Chinese (Traditional), Russian
Related Certifications:Microsoft Certified: Azure AI Fundamentals
Exam Duration:45-60
Exam Format:Multiple select, Scenario-based, Multiple choice, Match the service to use case, Drag and drop
Exam Price:USD 99
Sample Questions:Free Download Latest AI-901 Korean valid dump
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 computer vision workloads on Azure (15-20%)15-20%- Identify common types of computer vision solution
  • 1. Identify features of image classification solutions
  • 2. Identify features of semantic segmentation solutions
  • 3. Identify features of object detection solutions
  • 4. Identify features of image analysis solutions
  • 5. Identify features of face detection and identification solutions
  • 6. Identify features of optical character recognition (OCR) solutions
- 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
Describe features of generative AI workloads on Azure (20-25%)20-25%- 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
- Identify features of generative AI solutions
  • 1. Identify features of generative AI models
  • 2. Identify common scenarios for generative AI
  • 3. Identify responsible AI considerations for generative AI
Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)15-20%- Identify Azure tools and services for NLP workloads
  • 1. Describe capabilities of the Azure AI Language service
  • 2. Describe capabilities of the Azure AI Speech service
- Identify features of common NLP workload scenarios
  • 1. Identify features and uses for speech recognition and synthesis
  • 2. Identify features and uses for key phrase extraction
  • 3. Identify features and uses for sentiment analysis
  • 4. Identify features and uses for translation
  • 5. Identify features and uses for entity recognition
  • 6. Identify features and uses for language modeling
Describe Artificial Intelligence workloads and considerations (15-20%)15-20%- Identify features of common AI workloads
  • 1. Identify features of knowledge mining workloads
  • 2. Identify features of content moderation and moderation workloads
  • 3. Identify features of generative AI workloads
  • 4. Identify features of computer vision workloads
  • 5. Identify features of document intelligence workloads
  • 6. Identify features of Natural Language Processing (NLP) workloads
- Identify guiding principles for responsible AI
  • 1. Describe considerations for accountability in an AI solution
  • 2. Describe considerations for transparency 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 inclusiveness in an AI solution
Describe fundamental principles of machine learning on Azure (15-20%)15-20%- Identify common machine learning techniques
  • 1. Identify clustering machine learning scenarios
  • 2. Identify features of deep learning techniques
  • 3. Identify regression machine learning scenarios
  • 4. Identify classification machine learning scenarios
- 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
- Describe Azure Machine Learning capabilities
  • 1. Describe capabilities of automated machine learning
  • 2. Describe model management and deployment capabilities in Azure Machine Learning
  • 3. Describe data and compute services for data science and machine learning

Microsoft Azure AI Fundamentals (AI-901 Korean Version) FAQ: Clear Answers for Serious Candidates

The AI-901 Korean exam is Microsoft's official route to the Microsoft Certified: Azure AI Fundamentals certification (Fundamental level). For IT professionals building a career, it signals verified skill — the kind of advantage that tips better opportunities your way. It also sits in a family of related credentials: Microsoft Certified: Azure AI Fundamentals.

Delivery is instant — files unlock at payment and a copy lands in your email within a minute; our 24/7 online service team responds within 2 hours if anything goes missing, and there are no installation limits. On refunds, our guarantee is real but conditional: take the corresponding AI-901 Korean exam within 60 days of purchase, and if you fail, send a scanned enrollment slip plus the official Score Report PDF within 2 days of the exam — we process the full refund within 7 days. Exams taken within 3 days of purchase, name mismatches between candidate and payer, and free or expired products are excluded. Rather have a replacement? Exchange for two equal-value exam products free and keep your original updates.

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. Requirements like these do get updated, so confirm the details on the official exam page — official AI-901 Korean exam information — before you spend anything on registration.

Registration runs USD 99, and the pass mark is 700 / 1000. Paying by credit card is the standard route — safe and stable for both buyer and seller. And remember the fee is per attempt: a retake costs the same again, which is why candidates drill with the 132 practice questions from Actual4Dumps until their margin is comfortable.

The exam sets 40-60 questions against 45-60 on the clock. That pairing punishes hesitation, so train it out: set a per-question budget, flag-and-return instead of freezing, and rehearse full timed sessions in the Actual4Dumps engine until pacing is automatic.

Yes — a free PDF demo lets you examine the question quality first. If you buy, 365 days of free updates are included, with new versions sent to you as they're released; an expired update period can be renewed later at 50% off.

Expect 5 domains in the Microsoft Azure AI Fundamentals (AI-901 Korean Version) blueprint, headlined by Describe features of computer vision workloads on Azure (15-20%) (15-20%), Describe fundamental principles of machine learning on Azure (15-20%) (15-20%), Describe Artificial Intelligence workloads and considerations (15-20%) (15-20%). Use the weights as your study budget — high-percentage domains earn the most points per hour. The complete outline above has the full breakdown.

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

Question #1

Microsoft Foundry 프로젝트에 비전 기능을 지원하는 채팅 모델 배포가 포함되어 있습니다.
여러분은 응답 API를 사용하는 Python 애플리케이션을 개발하고 있습니다. 이 애플리케이션은 사용자 프롬프트와 로컬 JPEG 이미지를 포함하는 요청을 보냅니다.
요청에 로컬 이미지를 포함해야 합니다.
이미지 입력값으로 어떤 값을 사용해야 할까요?

  • A. https:// < your-storage-account > .core.windows.net/ < container > // < file > .jpg
  • B. C:\images\photo.jpg
  • C. 데이터:image/jpeg;base64, < 바이너리 이미지 데이터 >
  • D. file:///C:/images/photo.jpg
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #2

기사 텍스트를 기반으로 삽화를 생성하려면 어떤 유형의 Azure AI 워크로드를 사용해야 할까요?

  • A. Foundry Tools의 Azure Document Intelligence
  • B. 생성형 AI
  • C. 자연어 처리
  • D. 컴퓨터 비전
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

당신은 Foundry Tools의 Azure Content Understanding을 사용하여 음성 메일 녹음을 처리하는 애플리케이션을 개발하고 있습니다.
Azure Content Understanding은 오디오를 텍스트로 변환하기 위해 어떤 기능을 사용합니까?

  • A. 보이스 라이브
  • B. 광학 문자 인식(OCR)
  • C. 핵심 문구 추출
  • D. 전사
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #4

문장을 올바르게 완성하는 답을 고르시오.

Reveal Solution  Discussion  0

Correct Answer:


Explanation:

A schema defines which fields to extract when analyzing content.
In Azure Content Understanding, the schema or fieldSchema defines the structured data that the analyzer extracts from content, including field names, types, and extraction behavior. Microsoft documentation states that Content Understanding lets you define a schema to extract, classify, or generate field values from unstructured content.
The other options are incorrect:
A keyword list does not define the complete structured output fields.
OCR-only processing extracts text, but it does not define structured fields.
A synchronous API call describes a request pattern, not the extraction schema.

Question #5

다음 중 마이크로소프트의 책임 있는 AI 원칙의 예시는 무엇입니까?

  • A. AI 시스템은 이해하기 쉬워야 합니다.
  • B. AI 시스템은 회사의 이익을 보호해야 합니다.
  • C. AI 시스템은 공개적으로 이용 가능한 데이터만 사용해야 합니다.
  • D. AI 시스템은 개인 정보를 공개해야 합니다.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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