Microsoft AI-900 中文 : Microsoft Azure AI Fundamentals (AI-900中文版)

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Requisites of Microsoft AI-900 Exam

In order to take the Microsoft AI-900 exam, you must have a current Azure subscription. You also need a valid Microsoft ID. In addition, be sure to pass the following exams:

• AZ-200: Azure Fundamentals Assessment
• AZ-100: Fundamentals of Azure

Bottom Line

One groundbreaking tool for the past decade or so has been Artificial Intelligence (AI). And it feels good to see top-ranked companies and IT certification vendors such as Microsoft coming to the fore to help fast-track the latest developments around this field. One of the outstanding designations today is the Microsoft Certified: Azure AI Fundamentals, which is well suited to all trainees who are making their first steps in this sector. With the latest technologies, the demand for AI engineers is at an all-time high, with industry experts stating that the trend could go on for many years into the future. This could only mean one thing: now is the perfect time to get into this field. The Microsoft AI-900 exam with an updated curriculum will help you make a strong statement in this area so you’ll manage to focus on more advanced certifications at a later stage of your career. So, get started with the above-mentioned resources and become the best specialist you can be to reach the optimum heights in your professional life.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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Microsoft AI-900 中文 Exam Syllabus Topics:

Microsoft Azure AI Fundamentals (AI-900中文版) Sample Questions:

Question #1
你使用无人机来识别作物行间杂草的生长位置，并发送指令清除杂草。这属于哪种计算机视觉技术？

A. 光学字符识别(OCR)
B. 目标检测
C. 场景分割

Question #2
您需要產生用於小冊子的漫畫。每部漫畫都將基於文字描述。
您應該使用哪種 Azure OpenAI 模型？

A. DALL-E
B. GPT-4
C. 法典
D. GPT-3.5

Question #3
您需要根據照片中的街道標誌來識別街道名稱。
您應該使用哪種類型的電腦視覺？

A. 臉部辨識
B. 物體偵測
C. 光學字元辨識（OCR）
D. 影像分類

Question #4
將機器學習的類型與適當的場景相符。
要回答，請將適當的機器學習類型從左側列拖曳到右側的場景。每種機器學習類型可以使用一次、多次或完全不使用。
注意：每個正確的選擇都值得一分。

Question #5
您需要確定影像中汽車的位置，以便估計汽車之間的距離。
您應該使用哪種類型的電腦視覺？

A. 物體偵測
B. 光學字元辨識（OCR）
C. 人臉偵測
D. 影像分類

Solutions: