How to Register For Exam AI-900: Microsoft Azure AI Fundamentals?
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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One groundbreaking tool for the past decade or so has been Artificial Intelligence (AI). And it feels good to see top-ranked companies and IT certification vendors such as Microsoft coming to the fore to help fast-track the latest developments around this field. One of the outstanding designations today is the Microsoft Certified: Azure AI Fundamentals, which is well suited to all trainees who are making their first steps in this sector. With the latest technologies, the demand for AI engineers is at an all-time high, with industry experts stating that the trend could go on for many years into the future. This could only mean one thing: now is the perfect time to get into this field. The Microsoft AI-900 exam with an updated curriculum will help you make a strong statement in this area so you’ll manage to focus on more advanced certifications at a later stage of your career. So, get started with the above-mentioned resources and become the best specialist you can be to reach the optimum heights in your professional life.
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Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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 |
| 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 Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify Azure AI services for NLP - Describe Azure capabilities for NLP - Identify common NLP tasks |
| Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| 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 |
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