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Microsoft Azure AI Fundamentals Exam Certification Details:
| Passing Score | 700 / 1000 |
| Sample Questions | Microsoft Azure AI Fundamentals Sample Questions |
| Number of Questions | 40-60 |
| Exam Price | $99 (USD) |
| Duration | 60 mins |
| Exam Code | AI-900 |
| Exam Name | Microsoft Certified - Azure AI Fundamentals |
| Schedule Exam | Pearson VUE |
| Books / Training | Course AI-900T00: Microsoft Azure AI Fundamentals |
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Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi Arabia), Chinese (Traditional), Italian
Retirement date: none
Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; and features of conversational AI workloads on Azure.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Describe fundamental principles of machine learning on Azure | 30-35% | - Identify common machine learning tasks - Describe Azure Machine Learning capabilities - Describe core machine learning concepts - Describe features of no-code automated ML |
| Topic 2: Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify Azure AI services for NLP - Identify common NLP tasks - Describe Azure capabilities for NLP |
| Topic 3: Describe features of computer vision workloads on Azure | 15-20% | - Identify Azure AI services for computer vision - Describe Azure capabilities for computer vision - Identify common computer vision tasks |
| Topic 4: Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| Topic 5: Describe features of Generative AI workloads on Azure | 15-20% | - Identify responsible AI considerations for generative AI - Describe Azure OpenAI Service capabilities - Describe generative AI concepts |
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