Microsoft AI-900 中文 : Microsoft Azure AI Fundamentals (AI-900中文版)
- Exam Code: AI-900 中文
- Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
- Updated: Oct 24, 2026
- Q & A: 336 Questions and Answers
Theory becomes skill only through application. The VCETorrent AI-900 中文 package pairs 336 practice questions with engines that let you apply what you learn, fill the gaps that remain, and measure the progress between sessions.
Microsoft AI-900 中文 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamental principles of machine learning on Azure | 15–20% | - Describe capabilities of Azure Machine Learning - Describe automated machine learning - Describe core concepts of machine learning - Describe machine learning pipelines |
| Features of computer vision workloads on Azure | 15–20% | - Identify types of computer vision solutions - Describe capabilities of Azure Face - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision |
| Features of generative AI workloads on Azure | 20–25% | - Describe responsible AI practices for generative AI - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts |
| Artificial Intelligence workloads and considerations | 15–20% | - Describe responsible AI principles - Describe considerations for developing AI solutions - Identify types of AI workloads |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Identify types of NLP solutions - Describe capabilities of Azure Speech - Describe capabilities of Azure Language - Describe capabilities of Azure Translator |
AI-900 中文 Exam FAQ and Buying Guide
Microsoft recommends these training resources for the Microsoft Azure AI Fundamentals (AI-900中文版) exam:
Follow the training with steady self-testing — the 336 practice questions from VCETorrent help you apply theory and fill any gaps the training leaves.
The Microsoft Azure AI Fundamentals (AI-900中文版) exam contains 40–60 to complete within 45 minutes. Timed simulation in the VCETorrent Desktop Test Engine teaches that rhythm before exam day does.
The official Microsoft Azure AI Fundamentals (AI-900中文版) outline defines 5 domains. The leading three are Artificial Intelligence workloads and considerations (15–20%), Fundamental principles of machine learning on Azure (15–20%), and Features of computer vision workloads on Azure (15–20%). The full list is in the topics section above, and VCETorrent's 336 practice questions cover each one.
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. Earning the credential in 2026 can strengthen a career, and VCETorrent prepares candidates with 336 practice questions in PDF, Desktop Test Engine, and Online Test Engine formats.
Online proctored or onsite testing at Pearson VUE test centers Register for the Microsoft Azure AI Fundamentals (AI-900中文版) exam through these official channels:
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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 VCETorrent 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 that simulates the real exam with two practice modes and works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. Download the demo first, experience the materials, and choose the format you like best — 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.
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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.
Microsoft Azure AI Fundamentals (AI-900中文版) Sample Questions:
選出正確完成句子的答案。
Correct Answer:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of common machine learning types", regression is a supervised machine learning technique used to predict continuous numerical values based on one or more input features. In this scenario, the task is to predict a vehicle's miles per gallon (MPG)-a continuous numeric value-based on several measurable factors such as weight, engine power, and other specifications.
Regression models learn the mathematical relationship between input variables (independent features) and a numeric target variable (dependent outcome). Common regression algorithms include linear regression, decision tree regression, and support vector regression. In the example, the model would analyze historical data of vehicles and learn patterns that map characteristics (like engine size, horsepower, and weight) to fuel efficiency. Once trained, it can predict the MPG for a new vehicle configuration.
The other options describe different problem types:
* Classification predicts discrete categories (for example, whether a car is "fuel efficient" or "not fuel efficient"), not continuous values.
* Clustering is an unsupervised learning method that groups data points based on similarities without predefined labels, not predictive modeling.
* Anomaly detection identifies data points that significantly deviate from normal patterns, such as detecting engine sensor failures or fraudulent transactions.
Since predicting MPG involves estimating a numeric value within a continuous range, regression is the most appropriate model type.
In summary, per AI-900 training content, regression models are used when the output variable is numeric, classification for categorical outputs, and clustering for pattern discovery. Therefore, predicting miles per gallon based on vehicle features is a textbook example of a regression problem in Azure Machine Learning.
您應該使用哪種 AI 服務根據常見問題 (FAQ) 文件建立機器人？
- A. 文字分析
- B. QnA Maker
- C. 語言理解 (LUIS)
- D. 講話
Correct Answer: B 🗳️
Explanation: Only visible for VCETorrent members. You can sign-up / login (it's free).
您可以使用哪兩種資源來分析程式碼並產生程式碼函數和程式碼註解的解釋？每個正確答案都代表一個完整的解決方案。
注意：每個正確答案都值一分。
- A. Azure OpenAI Whisper 模型
- B. GitHub Copilot 服務
- C. Azure OpenAI GPT-4 模型
- D. Azure OpenAI DALL-E 模型
Correct Answer: B,C 🗳️
Explanation: Only visible for VCETorrent members. You can sign-up / login (it's free).
您需要建立叢集模型並使用 Azure 機器學習設計器評估該模型。你該怎麼辦？
- A. 將原始資料集拆分為訓練資料集和測試資料集。使用訓練資料集進行評估。
- B. 將原始資料集拆分為訓練資料集和測試資料集。使用測試資料集進行評估。
- C. 將原始資料集拆分為要素資料集和標籤資料集。使用特徵資料集進行評估。
- D. 使用原始資料集進行訓練和評估。
Correct Answer: B 🗳️
Explanation: Only visible for VCETorrent members. You can sign-up / login (it's free).
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:
Yes, Yes, No.
According to the Microsoft Azure AI Fundamentals (AI-900) study materials, conversational AI enables applications, websites, and digital assistants to interact with users via natural language. A chatbot is a key conversational AI workload and can be integrated into multiple channels such as web pages, Microsoft Teams, Facebook Messenger, and Cortana using Azure Bot Service and Bot Framework.
* "A restaurant can use a chatbot to answer queries through Cortana" - Yes.Azure Bot Service supports multi-channel deployment, which includes Cortana integration. This means the same bot can respond to voice or text input via Cortana, making it a valid use case for a restaurant to provide menu details, reservations, or order tracking through voice-based AI assistants.
* "A restaurant can use a chatbot to answer inquiries about business hours from a webpage" - Yes.This is a standard scenario for chatbots embedded on a company website. As per Microsoft Learn's Describe features of conversational AI module, a chatbot can be added to a website to handle FAQs such as business hours, location, or menu details, thereby improving response time and reducing repetitive human workload.
* "A restaurant can use a chatbot to automate responses to customer reviews on an external website" - No.Azure bots and other conversational AI tools cannot automatically interact with or post on external third-party platforms where the business does not control the data or API integration. Automated posting or replying to reviews on external review sites (e.g., Yelp or Google Reviews) would violate both ethical and technical boundaries of responsible AI usage outlined by Microsoft.
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