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所在平台: Udemy |
课程主页: https://www.udemy.com/course/effective-data-visualization/
课程评论：没有评论
课程名称：有效的数据可视化 课程概述： 本课程旨在帮助您通过有效的可视化方法将数据生动呈现。课程由Jefrey Heer（Trifacta的联合创始人）主讲, 他将带您了解设计交互式可视化、执行探索性数据分析以及研究多维数据的最佳实践。您将首先学习可视化的价值，结合来自图形设计、视觉艺术、感知心理学和认知科学的设计原则。通过Trifacta的数据转换工具来演示一些概念，您还将学习如何将可视化应用到极大数据集的技术。 本课程分为两个部分：有效的可视化设计和大数据可视化。您将获得实用技巧，涵盖以下主题： 1. 可视化设计基础：数据与图像模型、图形感知和颜色设计 2. 视觉数据分析与探究：探索性数据分析、多维数据与交互技巧 3. 数据降维策略：抽样、聚合和模型拟合 4. 大数据的有效可视化：可扩展的视觉编码方法和交互技巧 讲师Jefrey Heer是Trifacta公司的联合创始人及首席体验官。他曾在斯坦福大学计算机科学系任教多年，领导斯坦福可视化小组，创造了多种流行工具，包括D3.js（数据驱动文档）和Data Wrangler。目前，Jeff是华盛顿大学计算机科学与工程系的教员。
Learn the methods you need to bring data to life through effective visualizations. In this video course, host Jefrey Heer-co-founder of Trifacta-takes you through best practices for designing interactive visualizations, performing exploratory data analysis, and examining multidimensional data. You'll begin by learning the value of visualization, through design principles drawn from graphic design, visual art, perceptual psychology, and cognitive science. Using Trifacta's data transformation tools to illustrate some of the concepts, you'll also learn techniques for scaling visualizations to extremely large data sets. In two parts-Effective Visualization Design and Visualizing Big Data-this course will teach you practical tips on topics including: Visualization design fundamentals: data and image models, graphical perception, and color designVisual data analysis and exploration: exploratory data analysis, multidimensional data, interaction techniquesData reduction strategies: sampling, aggregation, and model fittingEffective visualization of big data: scalable visual encoding methods and interaction techniques Jefrey Heer is a co-founder and CXO (Chief Experience Officer) at Trifacta Inc. He spent many years as a professor of Computer Science at Stanford University, where he led the Stanford Visualization Group. His group created several popular tools, including D3.js (Data-Driven Documents) and Data Wrangler. Jeff is currently a faculty member of Computer Science & Engineering at the University of Washington.
