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| Section | Weight | Objectives |
|---|---|---|
| Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Describe Azure capabilities for NLP - Identify Azure AI services for NLP |
| Describe AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI - Identify features of common AI workloads |
| Describe fundamental principles of machine learning on Azure | 30-35% | - Describe Azure Machine Learning capabilities - Describe core machine learning concepts - Describe features of no-code automated ML - Identify common machine learning tasks |
| Describe features of computer vision workloads on Azure | 15-20% | - Identify Azure AI services for computer vision - Identify common computer vision tasks - Describe Azure capabilities for computer vision |
| Describe features of Generative AI workloads on Azure | 15-20% | - Identify responsible AI considerations for generative AI - Describe Azure OpenAI Service capabilities - Describe generative AI concepts |
Microsoft recommends these training resources for the Microsoft Azure AI Fundamentals (AI-900 Korean Version) exam:
Follow the training with steady self-testing — the 336 practice questions from Actual4Labs help you apply theory and fill any gaps the training leaves.
The official Microsoft Azure AI Fundamentals (AI-900 Korean Version) outline defines 5 domains. The leading three are Describe features of Generative AI workloads on Azure (15-20%), Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%), and Describe features of computer vision workloads on Azure (15-20%). The full list is in the topics section above, and Actual4Labs's 336 practice questions cover each one.
Online proctored exam or in-person testing center (Pearson VUE) Register for the Microsoft Azure AI Fundamentals (AI-900 Korean Version) exam through these official channels:
After booking, Actual4Labs delivers your practice questions within 1 minute — preparation starts the same day.
The Microsoft Azure AI Fundamentals (AI-900 Korean Version) exam contains 40-60 to complete within 45-60. Timed simulation in the Actual4Labs Desktop Test Engine teaches that rhythm before exam day does.
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The AI-900 Korean exam is a Microsoft certification exam validating the Microsoft Azure AI Fundamentals (AI-900 Korean Version) syllabus shown above. It belongs to these credential paths: Microsoft Certified: Azure AI Fundamentals. Candidates in 2026 prepare for it with Actual4Labs's 336 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
No formal prerequisites required. Basic knowledge of cloud computing concepts is recommended but not mandatory. Since requirements change over time, confirm the latest on the official Microsoft exam page before scheduling.
The Microsoft Azure AI Fundamentals (AI-900 Korean Version) exam requires 700/1000 to pass, and registration costs USD 99.00. A failed attempt means paying the same fee again — a readiness check with the Actual4Labs engines before booking is the cheaper option.
Three versions of the same study materials: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows with customizable simulation and timed modes that works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 336 practice questions are identical across versions. Every purchase includes 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.
이상 감지에 사용할 수 있는 머신 러닝 기술은 무엇입니까?
Correct Answer: C 🗳️
Explanation: Only visible for Actual4Labs members. You can sign-up / login (it's free).
자동차 사이의 거리를 추정하려면 이미지에서 자동차의 위치를 파악해야 합니다.
어떤 유형의 컴퓨터 비전을 사용해야 합니까?
Correct Answer: C 🗳️
Explanation: Only visible for Actual4Labs members. You can sign-up / login (it's free).
어떤 상황에서 핵심어 추출을 사용해야 할까요?
Correct Answer: D 🗳️
Explanation: Only visible for Actual4Labs members. You can sign-up / login (it's free).
문장을 올바르게 완성하는 답을 선택하세요.
Correct Answer:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) curriculum and Microsoft Learn's modules on Computer Vision, object detection is the AI technique used to identify and locate multiple objects within an image. Unlike simple image classification, which only labels an entire image with a single category (for example, "This is a product"), object detection not only identifies the type of object but also pinpoints its exact position by providing bounding boxes and coordinates within the image.
In the scenario described - identifying the location of products on a conveyor belt - the system must be able to detect multiple items simultaneously and determine their spatial positions. Object detection algorithms (such as YOLO, Faster R-CNN, or SSD) are specifically designed for this purpose. This allows automation systems, like robotic arms or quality inspection systems, to track product locations in real time for sorting, packaging, or defect detection.
Let's evaluate the other options:
* Image classification only determines what is in the image, not where it is located. It cannot handle multiple objects or their positions.
* Image processing involves operations like resizing, filtering, or adjusting contrast, not understanding object placement.
* Optical character recognition (OCR) extracts text from images and documents, unrelated to locating physical items.
Thus, per Microsoft Learn's AI-900 guidance, object detection is the correct computer vision capability when a task requires both identification and spatial localization of items in an image or video stream.
# Final answer Object detection
자연어 처리 작업 부하의 두 가지 예는 무엇입니까? 각 정답은 완전한 해결책을 제시합니다.
참고사항: 정답 하나당 1점입니다.
Correct Answer: A,B 🗳️
Explanation: Only visible for Actual4Labs members. You can sign-up / login (it's free).
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