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所在平台: Udemy |
课程主页: https://www.udemy.com/course/exam-ai-900-microsoft-azure-ai-fundamentals-s/
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课程名称：AI-900考试：Microsoft Azure AI基础 课程概述：本课程定期更新，以符合最新考试要求！欢迎参加高质量的练习测试，帮助您为AI-900 Microsoft Azure AI基础考试做好准备。该课程包含两个完整的计时测试，每个测试至少包含45道问题，与官方考试相似，共计90道题目，帮助您评估自己是否为真实考试做好准备。所有测验题目均根据考生公告中发布的领域权重进行了平衡。此外，在考试结束后，您可以查看自己的答案与正确答案的对比，并获得每道题目及选项的详细解释和文档链接，以及正确答案的推荐解答方式。这些练习测试旨在让您了解可能在考试中遇到的各种问题，这些问题基于以往考试和其他课程中的练习测试，确保您第一次尝试时就能顺利通过。 我强烈推荐您在参加真正的AI-900开发解决方案的Microsoft Azure考试之前，先参加AI-900的练习测试以验证您的学习成果。本AI-900练习测试课程旨在涵盖每个主题，难度水平与真实考试相当，让您全面准备AI-900 Azure数据基础考试。 AI-900考试主要涵盖以下主题： - 描述AI工作负载和注意事项（15-20%） - 描述Azure上机器学习的基本原则（30-35%） - 描述Azure上计算机视觉工作负载特征（15-20%） - 描述Azure上自然语言处理（NLP）工作负载特征（15-20%） - 描述Azure上会话AI工作负载特征（15-20%）
*This Course is Updated regularly to align with the latest exams!Welcome to the top quality practice tests to help you prepare for your AI-900 Microsoft Azure AI Fundamental Exam.This practice test course contains 2 complete timed tests, of at least 45-questions each, just like you will get in the official exam. That's 90 questions to see how prepared you are for the real test. The quiz questions are balanced as per the domain weightings published in the candidate bulletin. In addition, after taking the exam you can review your answers compared against the correct answers including comprehensive explanations and documentation links of each question, the answer options and the recommended approach for getting the answers right.This Practice Tests are meant to make you go through all kind of questions that Can occur during the exam, based on previous exams and so many other practice tests in other courses to make sure you pass in your first attempt.I strongly recommend to take AI-900 practice tests to validate your learning before taking the real AI-900 Developing Solutions for Microsoft Azure exam. This AI-900 practice test course is designed to cover every topic, with a difficulty level like a real exam.Complete preparation for the AI-900 Azure Data Fundamentals exam.The AI-900 exam covers the following topics:Describe AI workloads and considerations (15-20%)Describe fundamental principles of machine learning on Azure (30-35%)Describe features of computer vision workloads on Azure (15-20%)Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)Describe features of conversational AI workloads on Azure (15-20%)
