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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-900-exam/
课程评论：没有评论
课程名称：AI-900 Azure AI 基础知识考试准备（一天完成） 课程概述：本课程面向所有希望了解 Microsoft Azure AI 900 的新手，旨在帮助学员为考试做好准备。该课程将为学员提供有价值的学习体验。关于 AI 900，该课程旨在为学员提供人工智能概念及其在 Azure 中应用的基础理解，涵盖 AI 的基本原则、常见的 AI 工作负载以及在 Azure 中构建 AI 解决方案的可用服务。 目标受众：本课程适合刚接触人工智能并希望获得基本理解的人群，也对项目经理或销售代表等商业利益相关者有益，他们需要理解人工智能的能力以便做出明智的决策。 课程内容：AI 900 课程包括以下关键主题的实践测试： 1. 人工智能简介：理解基本概念、原则和人工智能的类型。 2. 机器学习：探索机器学习的概念，包括监督学习、无监督学习和强化学习。 3. 计算机视觉：理解计算机视觉及其应用，例如图像识别和物体检测。 4. 自然语言处理（NLP）：探索自然语言处理的概念，包括文本分析、情感分析和语言翻译。 5. 对话式人工智能：学习对话式人工智能技术，如聊天机器人和虚拟代理。 6. 负责任的人工智能：理解人工智能的伦理和负责任使用，包括公平性、透明性和隐私考虑。 7. Azure AI 服务：探索 Azure 中可用的人工智能服务，如 Azure 认知服务和 Azure 机器学习。
This course is for anyone who is new to Microsoft Azure AI 900 and is willing to take examination.I assure you that you will find this course very useful.About AI 900The AI-900 course is designed to provide a foundational understanding of AI concepts and their application in Azure. It covers the fundamental principles of AI, common AI workloads, and the services available in Azure for building AI solutions.Target Audience: The course is suitable for individuals who are new to AI and want to gain a basic understanding of AI concepts and how they can be implemented using Azure services. It is also beneficial for business stakeholders, such as project managers or sales representatives, who need to understand AI capabilities to make informed decisions.Course Content: The AI 900 course covers practice test for the following key topics:Introduction to AI: Understanding the basic concepts, principles, and types of AI.Machine Learning: Exploring machine learning concepts, including supervised, unsupervised, and reinforcement learning.Computer Vision: Understanding computer vision and its applications, such as image recognition and object detection.Natural Language Processing (NLP): Exploring NLP concepts, including text analysis, sentiment analysis, and language translation.Conversational AI: Learning about conversational AI technologies, such as chatbots and virtual agents.Responsible AI: Understanding the ethical and responsible use of AI, including fairness, transparency, and privacy considerations.Azure AI Services: Exploring the AI services available in Azure, such as Azure Cognitive Services and Azure Machine Learning.
