About Prep4sures Microsoft AI-900 中文 Exam
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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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Preparation Process
Microsoft offers a wide range of resources to help you prepare for your certification exam. The first step in the preparation process is to go through the topics in detail. This will enable you to understand the specific areas that are covered in the test. With this understanding, you can start to get the materials that will provide more knowledge on the objectives. Thus, Microsoft comes with two training options to help the candidates develop the required skills. These are free online training and instructor-led training.
- Free Online Training: The individuals can explore five free training tutorials that are available on the official exam webpage. They have a series of modules that focus on the specific domains of the test. These training tutorials are recommended for those candidates who are comfortable with the self-paced study. The topics of these manuals include the following options:
- Get Started with AI on Azure;
- Create No-Code Predictive Models with Azure ML;
- Explore NLP;
- Explore Computer Vision on Microsoft Azure;
- Explore Conversational Artificial Intelligence.
The students can find the details of these learning paths on the official website.
- Instructor-Led Training: The Microsoft Azure AI Fundamentals course is designed to help you gain the required skills to pass the exam and obtain the certification. It introduces the learners to the fundamental concepts of AI and the services available in Microsoft Azure that are useful in creating AI solutions. This training is delivered by the certified partners and its details can be found on the Microsoft website. It is important to mention that this course is designed to be combined with other online materials that are available on the Microsoft Learning platform.
- Practice Test: As a future examinee, you also have access to the official practice test to evaluate your understanding of the exam topics before taking the actual test. The link to this training tool can be found on the Microsoft website.
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 |
|---|---|---|
| Topic 1: Features of generative AI workloads on Azure | 20–25% | - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI - Describe use cases for generative AI - Describe generative AI concepts |
| Topic 2: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Speech - Describe capabilities of Azure Translator - Describe capabilities of Azure Language - Identify types of NLP solutions |
| Topic 3: Fundamental principles of machine learning on Azure | 15–20% | - Describe machine learning pipelines - Describe automated machine learning - Describe capabilities of Azure Machine Learning - Describe core concepts of machine learning |
| Topic 4: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Identify types of computer vision solutions - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision |
| Topic 5: Artificial Intelligence workloads and considerations | 15–20% | - Describe responsible AI principles - Identify types of AI workloads - Describe considerations for developing AI solutions |




