AI-901 Korean exam dumps

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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 28, 2026

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  • Total Questions: 132
  • Updated on: Oct 28, 2026
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  • Total Questions: 132
  • Updated on: Oct 28, 2026
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  • Total Questions: 132
  • Updated on: Oct 28, 2026
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In 2026, flexibility matters as much as content: college students, working professionals, and busy parents all prepare differently. PrepAwayETE meets that reality for the AI-901 Korean exam with 132 practice questions available in PDF, PC test engine, and online formats you can use whenever a free moment appears.

Microsoft AI-901 Korean Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals (AI-900) Exam
Exam Number:AI-900
Certificate Validity Period:Does not expire (Fundamentals certification)
Related Certifications:Microsoft Azure Data Fundamentals (DP-900)
Microsoft Azure Fundamentals (AZ-900)
Exam Duration:60 minutes
Exam Format:Multiple choice, Case study (limited), Multiple response, Drag and drop
Available Languages:German, Portuguese (Brazil), French, Chinese (Simplified), Korean, Spanish, Chinese (Traditional), English, Japanese
Exam Price:Approx. 99 USD (varies by region)
Passing Score:700 (out of 1000)
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: DOWNLOAD DEMO
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-901 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Describe fundamental principles of machine learning on Azure25-30%- Machine learning concepts
  • 1. Regression and classification
    • 2. Training and evaluation concepts
      • 3. Supervised vs unsupervised learning
        - Azure Machine Learning basics
        • 1. AutoML concepts
          • 2. Azure ML workspace components
            Topic 2: Describe features of natural language processing (NLP) workloads on Azure15-20%- Text analysis
            • 1. Language detection
              • 2. Sentiment analysis
                • 3. Key phrase extraction
                  - Azure NLP services
                  • 1. Speech services (speech-to-text, text-to-speech)
                    • 2. Azure AI Language
                      Topic 3: Describe features of computer vision workloads on Azure15-20%- Image analysis
                      • 1. Optical character recognition (OCR)
                        • 2. Object detection
                          • 3. Image classification
                            - Azure AI Vision services
                            • 1. Face detection and analysis (limited use cases)
                              • 2. Azure AI Vision
                                Topic 4: Describe features of generative AI workloads on Azure10-15%- Generative AI concepts
                                • 1. Large language models (LLMs)
                                  • 2. Prompt engineering basics
                                    • 3. Responsible use of generative AI
                                      - Azure OpenAI and generative services
                                      • 1. Use cases: chatbots, content generation, summarization
                                        • 2. Azure OpenAI Service capabilities
                                          Topic 5: Describe Artificial Intelligence workloads and considerations20-25%- Identify features of common AI workloads
                                          • 1. Conversational AI and chatbots
                                            • 2. Computer vision use cases
                                              • 3. Natural language processing use cases
                                                • 4. Document processing and extraction
                                                  - Responsible AI principles
                                                  • 1. Inclusiveness
                                                    • 2. Transparency and accountability
                                                      • 3. Fairness
                                                        • 4. Reliability and safety
                                                          • 5. Privacy and security

                                                            AI-901 Korean Exam Preparation FAQs

                                                            The Microsoft Azure AI Fundamentals (AI-901 Korean Version) exam contains 40-60 questions, and you will have 60 minutes minutes to complete them. Rehearsing with the same volume of questions under a timer builds the pacing habits that make exam day feel familiar.

                                                            The interactive test engine recreates the structure and pressure of the real testing experience, with the questions and verified answers presented the way you will see them on exam day. Working in that environment trains your timing and concentration, so nothing about the real AI-901 Korean exam feels unfamiliar.

                                                            This package includes 132 practice questions for the Microsoft Azure AI Fundamentals (AI-901 Korean Version) exam. Every answer is verified by an experienced team of experts who review the question bank regularly, so you can rely on what you study.

                                                            The Microsoft Azure AI Fundamentals (AI-901 Korean Version) exam is scored on a scale where 700 (out of 1000) is required to pass, and the official exam fee is Approx. 99 USD (varies by region).

                                                            No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended.

                                                            You can confirm the current eligibility requirements on the official AI-901 Korean exam page before you register.

                                                            Yes. The PDF version can be printed and read whenever you have a free moment, while the PC test engine and online version let you practice on a computer or smartphone wherever you are. Whether your study time comes early in the morning or in short breaks between commitments, the material adapts to your day instead of the other way around.

                                                            The Microsoft Azure AI Fundamentals (AI-901 Korean Version) practice questions are organized around the official exam objectives. Key topics include:

                                                            • Describe fundamental principles of machine learning on Azure (25-30%)
                                                            • Describe Artificial Intelligence workloads and considerations (20-25%)
                                                            • Describe features of natural language processing (NLP) workloads on Azure (15-20%)

                                                            Focusing on the core topics first keeps your preparation efficient instead of scattered.

                                                            Many candidates combine practice questions with official training. Recommended options include:

                                                            The Microsoft Azure AI Fundamentals (AI-901 Korean Version) exam requires a score of 700 (out of 1000) to pass, and the official registration fee is Approx. 99 USD (varies by region). Knowing both numbers up front helps you plan your preparation budget realistically.

                                                            You can register for the Microsoft Azure AI Fundamentals (AI-901 Korean Version) exam through the official channels:

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

                                                            귀사는 사용자에게 AI 시스템의 목적, 기능 및 한계에 대한 명확한 정보를 제공합니다. 이는 마이크로소프트의 책임 있는 AI 원칙 중 어떤 원칙에 해당하는 예시입니까?

                                                            • A. 신뢰성 및 안전성
                                                            • B. 책임성
                                                            • C. 투명성
                                                            • D. 공정성
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: C  🗳️

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

                                                            Microsoft Foundry에 gpt-image-1이라는 모델을 배포합니다.
                                                            애플리케이션이 OpenAI Images API를 사용하여 사용자 프롬프트에서 이미지를 생성할 수 있는지 확인해야 합니다.
                                                            파이썬 코드를 어떻게 완성해야 할까요? 정답을 선택하려면 답변란에서 적절한 옵션을 고르세요.
                                                            참고: 정답 하나당 1점입니다.

                                                            Reveal Solution  Discussion  0

                                                            Correct Answer:


                                                            Explanation:
                                                            images.generate
                                                            The canonical Python call is:
                                                            response = client.images.generate(
                                                            model= " gpt-image-1 " ,
                                                            prompt=prompt
                                                            )
                                                            The correct selection is images.generate . Microsoft's current Foundry documentation shows that image generation with a deployed GPT Image model uses the OpenAI Python SDK ' s Images API , specifically client.images.generate(). Microsoft provides an example using model= " gpt-image-1 " together with a text prompt, which directly corresponds to this scenario.
                                                            chat.completions.create is intended for chat-completion interactions rather than the standalone Images API.
                                                            images.create is not the documented Python SDK method for generating an image. responses.create belongs to the Responses API , which can also orchestrate image generation through an image-generation tool, but that is a different API pattern from the explicitly requested OpenAI Images API . Microsoft distinguishes the standalone image-generation API from image generation performed through the Responses API.
                                                            One important detail in the supplied exhibit is that it visually shows client.responses. before the dropdown.
                                                            Taken literally, client.responses.images.generate() would not be the documented syntax. For this question, the intended answer is clearly images.generate , yielding the documented form client.images.generate(...) .
                                                            Study Guide Reference: Microsoft Azure AI Fundamentals # Implement AI solutions by using Microsoft Foundry # Generative AI and image-generation models.

                                                            다음 각 문장에 대해, 문장이 사실이면 '예'를 선택하고, 그렇지 않으면 '아니요'를 선택하십시오.
                                                            참고: 정답 하나당 1점입니다.

                                                            Reveal Solution  Discussion  0

                                                            Correct Answer:


                                                            Explanation:

                                                            In Microsoft Foundry Agent Service, tool_choice controls whether and how an agent uses tools during a run.
                                                            Statement 1: Yes
                                                            Setting tool_choice to auto lets the agent/model decide whether to call a tool. This statement is true.
                                                            Statement 2: No
                                                            Setting tool_choice to none does not mean the model decides whether to call a tool. It means the model will not call a tool. This statement is false.
                                                            Statement 3: Yes
                                                            Setting tool_choice to required means the agent must call one or more tools during the run. This statement is true.
                                                            Microsoft documentation describes the tool_choice values as follows: auto allows the model to decide whether to call tools, none prevents tool calls, and required forces one or more tool calls.

                                                            귀사는 인공지능(AI) 활용을 위한 모범 사례를 검토하고 있습니다.
                                                            각 작업은 마이크로소프트의 책임 있는 AI 원칙 중 어떤 원칙에 해당하는 예시인가요? 정답을 맞추려면 해당 원칙을 올바른 작업으로 드래그하세요. 각 작업은 한 번, 여러 번 또는 전혀 사용되지 않을 수 있습니다. 내용을 보려면 창 사이의 분할 막대를 드래그하거나 스크롤해야 할 수도 있습니다.
                                                            참고: 정답 하나당 1점입니다.

                                                            Reveal Solution  Discussion  0

                                                            Correct Answer:


                                                            Explanation:
                                                            Fairness
                                                            Privacy and security
                                                            Transparency
                                                            Reliability and safety
                                                            Comprehensive and Detailed Explanation with all Azure AI documents: =
                                                            Evaluating model outputs to ensure that decisions are NOT biased against specific demographic groups:
                                                            Fairness
                                                            Microsoft's responsible AI principle of fairness means AI systems should treat people fairly and avoid unfair bias across demographic groups.
                                                            Encrypting sensitive customer data and restricting system access to authorized personnel: Privacy and security The privacy and security principle requires AI systems to protect personal and sensitive data and prevent unauthorized access.
                                                            Informing users when they are interacting with an AI system and explaining the system's capabilities and limitations: Transparency The transparency principle requires that people understand when they are interacting with AI and understand the system's purpose, capabilities, and limitations.
                                                            Testing AI systems under different conditions to reduce unexpected failures: Reliability and safety The reliability and safety principle means AI systems should operate reliably and safely, including through testing and validation under expected and unexpected conditions.

                                                            Azure 구독을 보유하고 계십니다.
                                                            송장에서 구조화된 데이터를 추출하려면 Foundry Tools에서 Azure Content Understanding을 사용해야 합니다.
                                                            무엇을 준비해야 할까요?

                                                            • A. Microsoft Foundry 리소스
                                                            • B. Azure OpenAI 리소스
                                                            • C. Azure AI 검색 서비스
                                                            • D. 마이크로소프트 파운드리 프로젝트
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: A  🗳️

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