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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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The AI-900 exam is an entry-level certification that provides a solid foundation for individuals who want to pursue more advanced AI certifications. AI-900-CN exam covers basic concepts such as AI workloads, machine learning, and computer vision, as well as more advanced topics like natural language processing and conversational AI. AI-900-CN exam is designed to test your technical knowledge of AI and your ability to apply AI concepts to solve real-world business problems.
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Microsoft AI-900 exam, also known as the Microsoft Azure AI Fundamentals exam, is an entry-level certification exam designed to validate a candidate's foundational knowledge of Artificial Intelligence (AI) and Machine Learning (ML) concepts, as well as their ability to work with Microsoft Azure's AI services. AI-900-CN exam is intended for individuals who are interested in learning about AI and ML principles and how they can be applied to solve business problems.
Microsoft AI-900 中文 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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 Translator - Describe capabilities of Azure Speech - Describe capabilities of Azure Language |
| Fundamental principles of machine learning on Azure | 15–20% | - Describe core concepts of machine learning - Describe automated machine learning - Describe capabilities of Azure Machine Learning - Describe machine learning pipelines |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer - Identify types of computer vision solutions |
| Features of generative AI workloads on Azure | 20–25% | - Describe generative AI concepts - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI |
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