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Requisites of Microsoft AI-900 Exam
In order to take the Microsoft AI-900 exam, you must have a current Azure subscription. You also need a valid Microsoft ID. In addition, be sure to pass the following exams:
- AZ-200: Azure Fundamentals Assessment
- AZ-100: Fundamentals of Azure
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
What is Microsoft AI-900 Exam
Microsoft AI-900 exam is designed for Microsoft partners who are certified by Microsoft to integrate Microsoft Azure Intelligent Solutions into their own products and solutions. Explore the objectives of the AI-900 exam. Protection of the Azure platform and its components. Reference architecture for Azure solutions. Implementation, configuration, and management of Azure services. Request, manage and monitor Azure services. Troubleshooting of Azure services. Microsoft AI-900 exam dumps exam tests Questions are designed to identify the exam takers level of competence in the functions, features, and services of Azure. Depth and Breadth of Knowledge. Processes and practices for developing and deploying intelligent solutions. Hope you like this article. Associate in IT, Eugene is an expert in the fields of software applications and internet technologies. Paying attention to the latest technology is the reason Eugene uses his knowledge of high-end computer systems, application programming, and data entry.
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Microsoft AI-900日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| Topic 2: 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 |
| Topic 3: Describe fundamental principles of machine learning on Azure | 30-35% | - Describe Azure Machine Learning capabilities - Describe core machine learning concepts - Identify common machine learning tasks - Describe features of no-code automated ML |
| Topic 4: 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 5: 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 |
