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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/datavisualization
课程评论：没有评论
课程名称：数据可视化 课程概述：本课程将教授数据挖掘的一般概念及其基本方法和应用。随后，将深入研究数据挖掘的一个子领域：模式发现。学员将学习模式发现的深入概念、方法及应用。此外，还将介绍基于模式的分类方法以及模式发现的一些有趣应用。课程提供机会，让学员学习并实践可扩展的模式发现方法，以处理大量交易数据，讨论模式评估指标，并研究挖掘多样化模式、序列模式和子图模式的方法。 课程大纲： 第一部分：第1周：计算机与人类 描述：本周模块将学习数据可视化的定义、用途，以及计算机如何显示信息。学员将探索不同类型的可视化以及人类如何感知信息。 第二部分：第2周：数值数据的可视化 描述：本周模块将重点讨论如何有效地可视化数据，包括将数据分配给适当的图表元素、使用图形符号、平行坐标和流图，以及应用设计和色彩原则，以使可视化更加引人注目和有效。 第三部分：第3周：非数值数据的可视化 描述：本周模块将教授如何可视化表示数据项之间关系的图形。同时，学员将学习如何使用数据集中未具体提供的坐标绘制数据。 第四部分：第4周：可视化仪表板 描述：本周模块将汇总所学知识，设计自己的大型数据集和仪表板的可视化系统。学员将创建并解读基于数据集的可视化，并应用用户界面设计技术，以创建有效的可视化系统。
Part: 1
Title:Week 1: The Computer and the Human
Description:In this week's module, you will learn what data visualization is, how it's used, and how computers display information. You'll also explore different types of visualization and how humans perceive information.
Part: 2
Title:Week 2: Visualization of Numerical Data
Description:In this week's module, you will start to think about how to visualize data effectively. This will include assigning data to appropriate chart elements, using glyphs, parallel coordinates, and streamgraphs, as well as implementing principles of design and color to make your visualizations more engaging and effective.
Part: 3
Title:Week 3: Visualization of Non-Numerical Data
Description:In this week's module, you will learn how to visualize graphs that depict relationships between data items. You'll also plot data using coordinates that are not specifically provided by the data set.
Part: 4
Title:Week 4: The Visualization Dashboard
Description:In this week's module, you will start to put together everything you've learned by designing your own visualization system for large datasets and dashboards. You'll create and interpret the visualization you created from your data set, and you'll also apply techniques from user-interface design to create an effective visualization system.
Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.
