Certification Topics of Microsoft AI-900 Exam
Our Microsoft AI-900 exam dumps covers the following objectives of Microsoft AI-900 Exam.
- Describe AI workloads and considerations (15-20%)
- Describe features of computer vision workloads on Azure (15-20%)
- Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
- Describe fundamental principles of machine learning on Azure (30-35%)
- Describe features of conversational AI workloads on Azure (15-20%)
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Certification Path of Microsoft AI-900 Exam
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Microsoft AI-900日本語 Exam Overview:
| Certification Vendor: | Microsoft |
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Available Languages: | English, Japanese, Chinese (Simplified), Korean, Spanish, French, German, Portuguese (Brazil), Indonesian |
| Certificate Validity Period: | No expiration (certification does not expire) |
| Exam Duration: | 45-60 |
| Passing Score: | 700/1000 |
| Exam Price: | USD 99.00 |
| Real Exam Qty: | 40-60 |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Exam Format: | Single-choice, Multiple-choice, True/False, Drag and drop, Sequence ordering |
| Sample Questions: | Microsoft AI-900日本語 Sample Questions |
| Exam Way: | Online proctored exam or in-person testing center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required. Basic knowledge of cloud computing concepts is recommended but not mandatory. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/certifications/exams/ai-900/ |
Microsoft AI-900日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe features of Generative AI workloads on Azure | 15-20% | - Describe generative AI concepts - Describe Azure OpenAI Service capabilities - Identify responsible AI considerations for generative AI |
| Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Describe Azure capabilities for NLP - Identify common NLP tasks - Identify Azure AI services for NLP |
| Describe features of computer vision workloads on Azure | 15-20% | - Identify Azure AI services for computer vision - Identify common computer vision tasks - Describe Azure capabilities for computer vision |
| Describe fundamental principles of machine learning on Azure | 30-35% | - Describe core machine learning concepts - Describe features of no-code automated ML - Describe Azure Machine Learning capabilities - Identify common machine learning tasks |
| Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |


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