Exam Code: AI-900-CN
Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
Updated: Nov 07, 2026
Q & A: 336 Questions and Answers
AI-900 中文 Free Demo download
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer - Identify types of computer vision solutions - Describe capabilities of Azure Face |
| Topic 2: Fundamental principles of machine learning on Azure | 15–20% | - Describe core concepts of machine learning - Describe capabilities of Azure Machine Learning - Describe machine learning pipelines - Describe automated machine learning |
| Topic 3: Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe generative AI concepts - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI |
| Topic 4: Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Identify types of AI workloads - Describe responsible AI principles |
| Topic 5: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Speech - Identify types of NLP solutions - Describe capabilities of Azure Translator - Describe capabilities of Azure Language |
The Microsoft Azure AI Fundamentals (AI-900中文版) exam contains 40–60 to complete within 45 minutes. Timed simulation in the PassTorrent Desktop Test Engine teaches that rhythm before exam day does.
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.
The official Microsoft Azure AI Fundamentals (AI-900中文版) outline defines 5 domains. The leading three are Features of computer vision workloads on Azure (15–20%), Artificial Intelligence workloads and considerations (15–20%), and Fundamental principles of machine learning on Azure (15–20%). The full list is in the topics section above, and PassTorrent's 336 practice questions cover each one.
The Microsoft Azure AI Fundamentals (AI-900中文版) exam requires 700 (on a scale of 1–1000) to pass, and registration costs $99 USD. A failed attempt means paying the same fee again — a readiness check with the PassTorrent engines before booking is the cheaper option.
The AI-900 中文 exam is a Microsoft certification exam validating the Microsoft Azure AI Fundamentals (AI-900中文版) syllabus shown above. It belongs to these credential paths: Microsoft Certified: Azure Data Fundamentals, Microsoft Certified: Azure Fundamentals. Candidates in 2026 keep up with it using PassTorrent'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.
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No required prerequisites; basic familiarity with cloud computing or AI concepts is recommended but not mandatory Since requirements change over time, confirm the latest on the official Microsoft exam page before scheduling.
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您可以使用哪種電腦視覺功能來為數位照片產生自動標題?
Correct Answer: D 🗳️
Explanation: Only visible for PassTorrent members. You can sign-up / login (it's free).
您需要預測一個地區的動物數量。
您應該使用哪種 Azure 機器學習類型?
Correct Answer: B 🗳️
Explanation: Only visible for PassTorrent members. You can sign-up / login (it's free).
您需要將收據轉換為電子表格中的交易。電子表格必須包含交易日期、商家的總支出以及已繳納的稅金。
您應該使用哪種 Azure Al 服務?
Correct Answer: B 🗳️
Explanation: Only visible for PassTorrent members. You can sign-up / login (it's free).
選出正確完成句子的答案。
Correct Answer:

Explanation:
The correct answer is Azure AI Custom Vision.
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Explore computer vision in Azure", the Azure AI Custom Vision service is specifically designed to allow users to train, test, and deploy custom image classification and object detection models using their own images.
The Azure AI Custom Vision service extends the capabilities of Azure's general-purpose Computer Vision API by enabling organizations to upload their own labeled datasets, define custom tags (labels), and train models that are optimized for their specific use cases. This makes it ideal for object detection scenarios-such as detecting equipment in a manufacturing line, identifying products on store shelves, or recognizing medical images-where general-purpose models may not suffice.
By contrast, the Azure AI Computer Vision service provides pre-built models for tasks such as image description, tagging, face detection, and OCR (optical character recognition). It does not allow users to train their own models with custom data. Similarly, Azure AI Document Intelligence is used for extracting structured information from documents (forms, receipts, invoices), and Azure Video Analyzer for Media focuses on analyzing video content for insights and metadata extraction.
The AI-900 study guide emphasizes that the Custom Vision service supports two key model types:
* Image Classification - categorizing entire images based on predefined tags.
* Object Detection - identifying and locating multiple objects within an image by drawing bounding boxes.
Therefore, when the question specifies "train an object detection model by using your own images," the correct Azure service is Azure AI Custom Vision, as it provides the necessary tools for training, evaluating, and deploying custom computer vision models tailored to a user's dataset.
Hence, the verified correct answer is: Azure AI Custom Vision.
對於以下每個陳述,如果該陳述為真,請選擇「是」。否則,選擇“否”。 注意:每個正確的選擇都值得一分。
Correct Answer:

Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Describe core concepts of machine learning on Azure", the Azure Machine Learning Designer is a drag-and-drop, no-code/low-code interface that allows users to build, test, and deploy machine learning models visually without needing to write extensive code.
* Drag-and-Drop Visual Canvas # YESThe Azure Machine Learning Designer indeed provides a graphical interface where users can connect prebuilt modules for data preprocessing, training, evaluation, and deployment. Microsoft documentation describes it as a "drag-and-drop visual environment that simplifies machine learning model creation." This allows beginners and business users to construct machine learning pipelines intuitively, confirming this statement as True.
* Save Progress as a Pipeline Draft # YESThe designer lets users save their current work as a pipeline draft, enabling them to pause and return later. Microsoft Learn explicitly states that you can "save and publish pipeline drafts before running or deploying them." This functionality ensures workflow continuity, collaboration, and version management-making this statement also True.
* Include Custom JavaScript Functions # NOThe Azure Machine Learning Designer allows the integration of Python scripts through the "Execute Python Script" module for custom logic, but it does not support JavaScript. Custom code in the designer environment is limited to Python, as the platform is built for data science and machine learning tasks typically handled in Python-based environments.
Therefore, this statement is False.
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