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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/microsoft-azure-machine-learning
课程评论：没有评论
课程名称：Microsoft Azure 机器学习 概述：机器学习是人工智能的核心，许多现代应用和服务依赖于预测机器学习模型。训练机器学习模型是一个反复迭代的过程，需要时间和计算资源。自动化机器学习能够简化这个过程。在本课程中，您将学习如何使用 Azure 机器学习创建和发布模型，而无需编写代码。 本课程将帮助您为 AI-900 认证考试做好准备，这是一个五门课程项目中的第二门课程，旨在为您参加 AI-900 认证考试做准备。课程内容涵盖 AI 基础考试领域所评估的核心概念和技能。该初学者课程适合那些刚刚开始使用 Microsoft Azure 的 IT 人员，希望了解 Microsoft Azure 的产品并获得实际操作经验。Microsoft Azure AI Fundamentals 还可以为其他基于 Azure 的角色认证（如 Microsoft Azure 数据科学家助理或 Microsoft Azure AI 工程师助理）做准备，但并不是这些认证的先决条件。 本课程适合拥有技术和非技术背景的候选人。数据科学和软件工程的经验不是必需的，但是一些基本的编程知识或经验会有所帮助。成功完成本课程需要有基本的计算机素养和英语语言能力。您应该熟悉基本的计算概念和术语，以及一般的技术概念，包括机器学习和人工智能的概念。 教学大纲： 1. 使用 Azure 机器学习中的自动化机器学习 - 描述：训练机器学习模型是一个反复迭代的过程，需要时间和计算资源。自动化机器学习可以帮助简化这一过程。在本模块中，您将学习如何识别不同类型的机器学习模型，以及如何使用 Azure 机器学习的自动化机器学习功能来训练和部署预测模型。 2. 使用 Azure 机器学习设计器创建回归模型 - 描述：回归是一种监督机器学习技术，用于预测数值。在本模块中，您将学习如何使用 Azure 机器学习设计器创建回归模型。 3. 使用 Azure AI 创建分类模型 - 描述：分类是一种监督机器学习技术，用于预测类别或类。在本模块中，您将学习如何使用 Azure 机器学习设计器创建分类模型。 4. 使用 Azure AI 创建聚类模型 - 描述：聚类是一种无监督机器学习技术，用于根据特征对相似实体进行分组。在本模块中，您将学习如何使用 Azure 机器学习设计器创建聚类模型。
Name:Use Automated Machine Learning in Azure Machine Learning
Description:Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this module, you'll learn how to identify different kinds of machine learning model and how to use the automated machine learning capability of Azure Machine Learning to train and deploy a predictive model.
Name:Create a Regression Model with Azure Machine Learning Designer
Description:Regression is a supervised machine learning technique used to predict numeric values. in this module, you will learn how to create regression models using Azure Machine Learning designer.
Name:Create a Classification Model with Azure AI
Description:Classification is a supervised machine learning technique used to predict categories or classes. In this module, you will learn how to create classification models using Azure Machine Learning designer.
Name:Create a Clustering Model with Azure AI
Description:Clustering is an unsupervised machine learning technique used to group similar entities based on their features. In this module, you will learn how to create clustering models using Azure Machine Learning designer.
Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this course, you will learn how to use Azure Machine Learning to create and publish models without writing code. This course will help you prepare for Exam AI-900: Microsoft Azure AI Fundamentals. This is the second course in a five-course program that prepares you to take the AI-900 certification exam. This course teaches you the core concepts and skills that are assessed in the AI fundamentals exam domains. This beginner course is suitable for IT personnel who are just beginning to work with Microsoft Azure and want to learn about Microsoft Azure offerings and get hands-on experience with the product. Microsoft Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Microsoft Azure Data Scientist Associate or Microsoft Azure AI Engineer Associate, but it is not a prerequisite for any of them. This course is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience is not required; however, some general programming knowledge or experience would be beneficial. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. You should be familiar with basic computing concepts and terminology, general technology concepts, including concepts of machine learning and artificial intelligence.
