Prerequisites
Microsoft AI-900 is a foundational-level certification exam. Therefore, the potential candidates are required to possess basic knowledge of the AI and ML concepts. They also need to have an understanding of the associated Microsoft Azure services. These individuals can have technical or non-technical backgrounds. They do not need to have software engineering or science experience before taking the test. However, some programming experience or knowledge would be an advantage for them.
The AI-900 exam is designed to validate the students’ knowledge of AI workloads & considerations, as well as attributes of computer vision workloads within Azure. It also certifies their understanding of the basic principles of ML on Azure and attributes of conversational Artificial Intelligence workloads on Azure. The applicants are also required to demonstrate their knowledge of the attributes of NLP (Natural Language Processing) workloads on Azure.
The Need for Microsoft AI-900 Exam
The technologies that are tested on Microsoft AI-900 exam are necessary to develop intelligent operations based on cloud computing. Audience for this certification exam is individuals who work as computer programmers, developers, system administrators and project managers. Built for high-volume, high-speed web applications that use Azure, this Examines the skills required to develop intelligent cloud solutions. Smarter IT environments are the goal of this exam. Single sign-on for Azure, is an exam objective. Microsoft AI-900 exam dumps helps to make it easier for students to get this certification. Outline the business value of the exam. The importance of having this certification. Identify the technologies covered on Microsoft AI-900 exam. Gain a better understanding of the skills you'll need to develop intelligent cloud solutions.
Incredible opportunities are associated with this certification. Background on Azure and its products, services, networks, and the scalability of its computing infrastructure. Background of cloud computing in general. Automatically configure Azure virtual machines. Implement and configure SQL Server Integration Services (SSIS), Visual Studio Team Services (VSTS) and other Microsoft technologies. Predict the effects of each of the possible outcomes of the solution design. Led you to the final test. Ability to perform automated deployment of Azure services.
Workers who take this exam should have experience in the IT industry and should understand the architecture and business requirements of Azure. Leave no stone unturned. Personalized study plan for self-paced learning. Tests your knowledge in the whole Cloud Computing path from Azure to Office 365.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe core concepts of machine learning - Describe capabilities of Azure Machine Learning - Describe machine learning pipelines |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Identify types of NLP solutions - Describe capabilities of Azure Language - Describe capabilities of Azure Speech - Describe capabilities of Azure Translator |
| Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe considerations for developing AI solutions - Describe responsible AI principles |
| Features of computer vision workloads on Azure | 15–20% | - Identify types of computer vision solutions - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Face - Describe capabilities of Azure Custom Vision |
| Features of generative AI workloads on Azure | 20–25% | - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts - Describe use cases for generative AI - Describe responsible AI practices for generative AI |






