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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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The exam cost of Microsoft Azure AI Fundamentals is 99 USD.
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Objective of Microsoft AI-900 Exam
It's important to note that the Microsoft AI-900 exam isn't an exam on Azure; the objective of the exam is to make sure you know how to build and manage intelligent cloud solutions and services on Azure. Foundation to Azure, or you can still get the certificate. Defined best practices for solution design, deployment, and administration. Identity of Azure services. Conclude testing by connecting the solution to the infrastructure to test for functionality. Instructor for the exam has extensive experience with Azure. Textidentify Azure services. Define identity of Azure services. Rewarding in the form of free exam vouchers and in-demand credential. Microsoft AI-900 exam dumps prepare you to become qualified Azure solutions specialist. Focus on the skills that are of high value in your organization. Bots are an important part of this exam.
Pay special attention to Cloud design principles. Terms used to describe the Azure platform. Standing out in the crowd and getting the job you want. Regular updates by Microsoft experts. Space for comments with every question. Sources for determining Azure pricing. Document your approach to meeting your goals. Positive impact of the exam on your career path.
Microsoft AI-900日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe fundamental principles of machine learning on Azure | 30-35% | - Identify common machine learning tasks - Describe Azure Machine Learning capabilities - Describe features of no-code automated ML - Describe core machine learning concepts |
| 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 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 AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI - Identify features of common AI workloads |
| 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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