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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Exam AI-900: Microsoft Azure AI Fundamentals
Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.
This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.
This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.
Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.
Part of the requirements for: Microsoft Certified: Azure AI Fundamentals
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Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe features of computer vision workloads on Azure | 15-20% | - Describe Azure capabilities for computer vision - Identify Azure AI services for computer vision - Identify common computer vision tasks |
| Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Describe Azure capabilities for NLP - Identify Azure AI services for NLP |
| Describe fundamental principles of machine learning on Azure | 30-35% | - Identify common machine learning tasks - Describe core machine learning concepts - Describe Azure Machine Learning capabilities - Describe features of no-code automated ML |
| Describe features of Generative AI workloads on Azure | 15-20% | - Describe Azure OpenAI Service capabilities - Describe generative AI concepts - Identify responsible AI considerations for generative AI |
| Describe AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI - Identify features of common AI workloads |
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