Microsoft Azure is one of the leading cloud platforms that offer a wide range of AI and ML services to help organizations build intelligent applications. By becoming certified in AI-900, individuals can demonstrate their proficiency in AI and ML concepts and their ability to utilize Azure services to build intelligent applications. Moreover, this certification can help individuals advance their career in AI and ML and can serve as a stepping stone to more advanced certifications in the field.
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The Microsoft AI-900-KR exam is aimed at professionals who are involved in the development and implementation of AI solutions using Microsoft Azure. This includes data scientists, AI engineers, solution architects, and software developers. AI-900-KR exam is also ideal for business leaders who want to understand the potential of AI and how it can be used to drive innovation and growth.
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Certification Path
The Azure AI Fundamentals certification might not be a prerequisite for any other certification levels, however, it can still be used to prepare for multiple Azure-related qualifications including the Microsoft Certified: Azure Data Scientist Associate and the Microsoft Certified: Azure AI Engineer Associate.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Microsoft AI-900, also known as the Microsoft Azure AI Fundamentals exam, is a certification exam designed to test one's knowledge and understanding of the fundamentals of artificial intelligence (AI) and its application on the Microsoft Azure platform. Microsoft Azure AI Fundamentals (AI-900 Korean Version) certification exam is ideal for individuals who are interested in pursuing a career in AI or who want to demonstrate their expertise in AI to potential employers.
Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|






