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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/predictive-analytics-data-mining
课程评论：没有评论
课程名称：预测分析与数据挖掘 课程概述： 该课程旨在向学生介绍商业分析的科学，同时关注数字空间中数字的艺术性使用。其目标是为商业和管理者提供应用数据分析解决现实挑战所需的基础知识。学生将学习如何识别适合自身需求的分析工具，了解有效可靠的数据收集、分析和可视化方法，并在其机构、组织或客户的决策中利用数据。 课程大纲： 第一部分： 标题：模块0：准备工作与模块1：数据泛滥，知识匮乏 描述：本模块介绍最常用的重要无监督学习技术——聚类。学习结束后，学生将理解聚类分析的不同应用以及何时需要聚类及其重要性，还将接触到多种聚类方法。 第二部分： 标题：模块2：决策树 描述：本模块将讨论如何使用决策树表示知识，最后介绍随机森林方法，该方法克服了单个决策树在数据构造中存在的一些局限性（如高方差或低精度）。 第三部分： 标题：模块3：规则、规则及更多规则 描述：本模块关注三个关键主题，即规则、最近邻方法和贝叶斯方法。学生将了解规则在数据世界中的重要性，以及这些主题在数据分类分析中的应用。 第四部分： 标题：模块4：模型性能与推荐系统 描述：在本模块中，学生将研究识别推荐内容的工具，并识别交叉销售或增销机会。作为课程的最后一个模块，将总结之前的内容，并为学生提供自行实践的机会，学习如何调整这些模型以推动自己组织的业务影响。
Part: 1
Title:Module 0: Get Ready & Module 1: Drowning in Data, Starving for Knowledge
Description:This module will introduce you to the most common and important unsupervised learning technique – Clustering. You will have an understanding of different applications of clustering analysis after this module. You will also learn when we need clustering and why it is important. Then, you will be introduced to a variety of clustering methods.
Part: 2
Title:Module 2: Decision Trees
Description:In this module, we will discuss how to use decision trees to represent knowledge. The module concludes with a presentation of the Random Forest method that overcomes some of the limitations (such as high variance or low precision) of a single decision tree constructed from data.
Part: 3
Title:Module 3: Rules, Rules, and More Rules
Description:This module will focus on three key topics, namely rules, nearest neighbor methods, and Bayesian methods. Over the course of this module, you will be exposed to how rules factor into the world of data and how they play a role in the analysis of data. The second and third topics focus on the classification of data.
Part: 4
Title:Module 4: Model Performance and Recommendation Systems
Description:In this module, you will study tools for recognizing what to recommend, and identify cross-sell or upsell opportunities. As the last module of the course, we will wrap up the content so far and you will get an opportunity to practice on your own and learn how to adapt these models to drive business impact in your own organizations.
This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.
