Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Azure AI Fundamentals
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Microsoft Azure AI Fundamentals (AI-900中文版): AI-900 Exam
"Microsoft Azure AI Fundamentals (AI-900中文版)", also known as AI-900 exam, is a Microsoft Certification. With the complete collection of questions and answers, iPassleader has assembled to take you through 336 Q&As to your AI-900 Exam preparation. In the AI-900 exam resources, you will cover every field and category in Microsoft Certified: Azure AI Fundamentals Certification helping to ready you for your successful Microsoft Certification.
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- Updated on: Oct 16, 2026
- No. of Questions: 336 Questions & Answers
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- Updated on: Oct 16, 2026
- No. of Questions: 336 Questions & Answers
Certification content shifts with the industry, and iPassleader shifts with it. Our experts compile and refresh the AI-900 中文 bank according to current trends, so the Microsoft Azure AI Fundamentals (AI-900中文版) questions you practice reflect what the exam actually asks in 2026.
Microsoft AI-900 中文 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Passing Score: | 700/1000 |
| Exam Duration: | 45-60 |
| Real Exam Qty: | 40-60 |
| Available Languages: | English, Spanish, Indonesian, German, Chinese (Simplified), Korean, French, Japanese, Portuguese (Brazil) |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Exam Format: | Single-choice, Sequence ordering, Drag and drop, Multiple-choice, True/False |
| Exam Price: | USD 99.00 |
| Certificate Validity Period: | No expiration (certification does not expire) |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam or in-person testing center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required. Basic knowledge of cloud computing concepts is recommended but not mandatory. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/certifications/exams/ai-900/ |
Microsoft AI-900 中文 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe fundamental principles of machine learning on Azure | 30-35% | - Describe core machine learning concepts - Describe features of no-code automated ML - Identify common machine learning tasks - Describe Azure Machine Learning capabilities |
| Describe features of computer vision workloads on Azure | 15-20% | - Identify common computer vision tasks - Identify Azure AI services for computer vision - Describe Azure capabilities for computer vision |
| Describe AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI - Identify features of common AI workloads |
| Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Identify Azure AI services for NLP - Describe Azure capabilities for NLP |
| Describe features of Generative AI workloads on Azure | 15-20% | - Describe generative AI concepts - Describe Azure OpenAI Service capabilities - Identify responsible AI considerations for generative AI |
AI-900 中文 Questions Answered: Format, Cost, and Prep
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Microsoft sets the following prerequisites for the Microsoft Azure AI Fundamentals (AI-900中文版): No formal prerequisites required. Basic knowledge of cloud computing concepts is recommended but not mandatory..
Confirm the current requirements on the official certification page before booking.
The Microsoft Azure AI Fundamentals (AI-900中文版) blueprint is organized into these main domains:
- Describe features of Generative AI workloads on Azure (15-20%)
- Describe fundamental principles of machine learning on Azure (30-35%)
- Describe features of computer vision workloads on Azure (15-20%)
Further domains complete the official outline, and our question bank spans all of them.
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According to the latest exam information, the AI-900 中文 exam contains 40-60 questions and runs for 45-60 minutes. Timing yourself during practice sessions is a smart habit — pacing problems sink more candidates than knowledge gaps.
At present, the passing score for the AI-900 中文 exam is 700/1000 and the registration fee is USD 99.00. Both figures are set by Microsoft and can change, so double-check them on the official site when you register.
Microsoft Azure AI Fundamentals (AI-900中文版) Sample Questions:
您正在開發一個模型來使用分類來預測事件。
您有一個根據測試資料評分的模型的混淆矩陣，如下圖所示。
使用下拉式選單選擇答案選項，根據圖形中顯示的資訊完成每個陳述。
注意：每個正確的選擇都值得一分。
Correct Answer:
Explanation:
Box 1: 11
TP = True Positive.
The class labels in the training set can take on only two possible values, which we usually refer to as positive or negative. The positive and negative instances that a classifier predicts correctly are called true positives (TP) and true negatives (TN), respectively. Similarly, the incorrectly classified instances are called false positives (FP) and false negatives (FN).
Box 2: 1,033
FN = False Negative
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance Finding TP is easy. It basically means the value where Predicted and True value is 1 and that is 11 in this case.
False Negative means where true value was 1 but predicted value was 0 and that is 1033 in this case The confusion matrix shows cases where both the predicted and actual values were 1 (known as true positives) at the top left, and cases where both the predicted and the actual values were 0 (true negatives) at the bottom right. The other cells show cases where the predicted and actual values differ (false positives and false negatives).
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer
/evaluate-model
您有以下應用程式：
* App1：使用一組圖像和照片提取品牌名稱
* App2：實現建築物的非接觸式存取控制
每個應用程式使用哪種 Azure Al Vision 服務？要回答這個問題，請在答案區域中選擇相應的選項。
注意：每個正確選擇值一分。
Correct Answer:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn documentation on Azure AI Vision services, different Azure AI Vision capabilities are suited for different use cases such as object detection, brand recognition, facial recognition, and spatial analysis.
* App1: Uses a set of images and photos to extract brand names # Image AnalysisThe Azure AI Vision - Image Analysis service (formerly part of Computer Vision) can detect and extract brands, objects, text, and other visual features from images. It uses advanced image classification and object detection models to recognize logos and identify brand names (for example, "Microsoft" or "Coca-Cola") in photos. The Image Analysis API can also return descriptive tags, scene descriptions, and confidence scores. Therefore, since App1 analyzes static images to extract brand names, it specifically relies on the Image Analysis feature of Azure AI Vision.
* App2: Enables touchless access control for buildings # FaceThe Azure AI Face service is designed for facial detection, verification, and identification. It can recognize and match faces in real time, making it ideal for access control, identity verification, and attendance tracking systems. A "touchless access control" system uses a camera to detect a person's face and verify identity against a stored profile, allowing or denying entry without physical interaction.
The other options are not suitable:
* Optical Character Recognition (OCR) extracts text, not brand logos.
* Spatial Analysis is for detecting movement or presence in video feeds.
* Video Analysis is for analyzing dynamic video content rather than still images.
您需要為網站開發一個聊天機器人。聊天機器人必須根據以下文件中的資訊回答使用者的問題：
Microsoft Word 文件中的產品故障排除指南
網頁上的常見問題 (FAQ) 列表
您應該使用哪種服務來處理文件？
- A. QnA Maker
- B. Azure 機器人服務
- C. 語言理解
- D. 文字分析
Correct Answer: A 🗳️
Explanation: Only visible for iPassleader members. You can sign-up / login (it's free).
將 Azure 認知服務服務與適當的操作相符。
若要回答，請將對應的服務從左側的列拖曳到右側的操作。每項服務可能使用一次、多次或完全不使用。
注意：每場正確的比賽都值得一分。
Correct Answer:
Explanation:
These matches are based on the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore Azure Cognitive Services." Microsoft Azure provides Cognitive Services that enable developers to integrate artificial intelligence capabilities-such as vision, speech, language understanding, and decision-making-into applications without requiring in-depth AI expertise.
* Convert a user's speech to text # Speech ServiceThe Azure Speech Service supports speech-to-text (STT) conversion, which transcribes spoken language into written text. This feature is commonly used in voice assistants, transcription systems, and voice-enabled apps. The service uses advanced speech recognition models to handle different accents, languages, and background noises.
* Identify a user's intent # Language ServiceThe Azure AI Language Service (which includes capabilities from LUIS - Language Understanding) is used to interpret what a user means or wants to achieve based on their words. It identifies intents (the goal or action behind the input) and entities (key pieces of information) from natural language text. This is a key component in conversational AI applications, allowing chatbots and virtual assistants to respond intelligently.
* Provide a spoken response to the user # Speech ServiceThe Speech Service also supports text-to-speech (TTS) functionality, which converts textual responses into natural-sounding speech. This enables applications to communicate audibly with users, completing the conversational loop.
Translator Text is not used here because it's primarily designed for language translation between different languages, not for speech recognition or intent understanding.
您需要識別資料集中具有相似數值的行組。您應該使用哪種類型的機器學習？
- A. 回歸
- B. 聚類
- C. 分類
Correct Answer: B 🗳️
Explanation: Only visible for iPassleader members. You can sign-up / login (it's free).
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