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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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
The benefit of obtaining the AI-900: Microsoft Azure AI Fundamentals Exam Certification
For people working in technology, having an Azure certification becomes important. The high demand for Azure certified experts, the high salary and benefits. Microsoft Azure AI Fundamentals Exam Certification give you skills and knowledge about a particular area of technology.
The benefit that you receive after passing the AI-900: Microsoft Azure AI Fundamentals Exam Outlook and Modules is greater than the effort which you put in to pass this exam. Provide you a growth in terms of your knowledge and will open many opportunities for you. Sentiment of the IT companies will increase because of your skilled work. Candidates who are verified with the AI-900: Microsoft Azure AI Fundamentals Exam will get an advantage in job interviews. Sites such as Microsoft Learning comes with a collection of certifications, tips and articles which you can use to prepare for the exam.
Subjects of the test can be found on Microsoft Learning website. Clustering of data is one of the most important task on AI. It is used for improving accuracy. Labels are used to achieve this. Journey map is used to achieve this. Data grouping is used to achieve this. Validation is a process of finding what the probabilities are for the data to contain a given property. Remember to take the exam as early as possible.
Guides, strategies and testimonials you can find on the internet about the exam. Helpful to deal with the challenges in the exam. Attempt to use the free copies of the Microsoft Office Excel for this exam. Modeling approach for this exam is to use the AI technology through an artificial neural network.
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Microsoft AI-900 中文 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Identify types of AI workloads - Describe responsible AI principles |
| Fundamental principles of machine learning on Azure | 15–20% | - Describe core concepts of machine learning - Describe automated machine learning - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning |
| Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI - Describe generative AI concepts |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Speech - Describe capabilities of Azure Language - Describe capabilities of Azure Translator - Identify types of NLP solutions |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Form Recognizer |
