The AI-900 exam is suitable for individuals who are looking to develop their skills and knowledge in AI and machine learning, regardless of their background or experience level. AI-900-CN exam is also ideal for students who are interested in pursuing a career in AI and want to gain a fundamental understanding of the technology. For professionals, the AI-900 exam can help you demonstrate your knowledge and expertise in AI, which can lead to better job opportunities and higher salaries.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Microsoft AI-900 Exam is an entry-level certification exam that does not require any prerequisites. However, candidates should have a basic understanding of cloud computing and Microsoft Azure. AI-900-CN exam consists of 40-60 multiple-choice questions, and candidates have 60 minutes to complete it. Upon passing the exam, candidates will receive the Microsoft Certified: Azure AI Fundamentals certification, which is a valuable credential in the AI industry.
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Microsoft AI-900 中文 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe capabilities of Azure Machine Learning - Describe core concepts of machine learning - Describe machine learning pipelines |
| Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe responsible AI principles - Describe considerations for developing AI solutions |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision - Identify types of computer vision solutions - Describe capabilities of Azure Computer Vision |
| Features of generative AI workloads on Azure | 20–25% | - Describe generative AI concepts - Describe responsible AI practices for generative AI - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service |
| 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 |
