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Exam AI-900: Microsoft Azure AI Fundamentals
Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.
This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.
This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.
Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.
Part of the requirements for: Microsoft Certified: Azure AI Fundamentals
Microsoft AI-900 Practice Test Questions, Microsoft AI-900 Exam Practice Test Questions
The individuals who passed the Microsoft AI-900 exam possess the foundational knowledge of artificial intelligence (AI) and machine learning (ML). The test is designed to evaluate the candidates’ understanding of basic AI and ML workloads as well as how to execute them on Microsoft Azure. The students can earn the Microsoft Certified: Azure AI Fundamentals certification at the end of their journey with this path.
Introducing Updated Microsoft Certified: Azure AI Fundamentals Designation
This certificate is an opportunity for candidates to showcase their mastery of the Machine Learning (ML) and Artificial Intelligence (AI) workloads and their implementation of Azure services. For that reason, AI-900 exam can be taken by all candidates from technical and non-technical fields. While software engineering and data science skills may not be required for such an evaluation, it is important to have general programming knowledge to stand a chance of cracking this test right away. By and large, the updated Microsoft Certified: Azure AI Fundamentals designation can help you advance your career growth by preparing you for advanced Azure role-based certifications including the Microsoft Certified: Azure AI Engineer Associate and the Microsoft Certified: Azure Data Scientist Associate certificates.
Exam Details
The Microsoft AI-900 exam is the only qualifying test that leads to the Microsoft Certified: Azure AI Fundamentals certification. It measures one’s knowledge of AI considerations & workloads, features of NLP workloads on Azure, and basic principles of ML on Azure. The candidates can choose to take this exam in English, French, Simplified Chinese, Japanese, German, Spanish, or Korean. It contains 40-60 questions covering different types, including case studies, drag and drop, active screen, build list, and multiple choice. You can schedule your test with Certiport or Pearson VUE. However, it is required to pay the fee of $99 before scheduling it.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Microsoft AI-900 中文 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer |
| Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Identify types of AI workloads - Describe responsible AI principles |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Language - Identify types of NLP solutions - Describe capabilities of Azure Translator - Describe capabilities of Azure Speech |
| Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe generative AI concepts - Describe responsible AI practices for generative AI - Describe capabilities of Azure OpenAI Service |
| Fundamental principles of machine learning on Azure | 15–20% | - Describe capabilities of Azure Machine Learning - Describe automated machine learning - Describe core concepts of machine learning - Describe machine learning pipelines |
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