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所在平台: Udemy |
课程主页: https://www.udemy.com/course/info-vis/
课程评论：没有评论
Coursera 课程：信息可视化 **课程概述：** 随着数据量的爆炸式增长，有效的可视化已成为理解复杂信息的关键。人类视觉感知能力强大，能够轻易解读复杂现象。信息可视化旨在创建易于理解和沟通的视觉表示，帮助用户探索海量数据中的隐藏信息，并提供比单纯统计分析更可靠的洞察。可视化还能促进更有效和交互式的规划。 本课程面向计算机科学、工程、数学、经济学及商科等不同背景的学生，旨在全面涵盖信息可视化的核心主题。 **核心主题：** * 信息可视化的动机与目的 * 通过案例学习信息可视化 * 数据表示、描述与数据类型 * 数据集类型与属性类型 * 图表设计与视觉编码 * 信息可视化中的色彩运用 * 可视化流程与人类感知 * 基于示例的分析 * 交互设计 * 可视化管线与技术 * 设计视觉用户界面 * 信息可视化中的验证 * 地理数据可视化 * 网络与树状结构可视化 **学习目标：** 完成本课程后，学生将能够： * 掌握信息可视化的基本概念。 * 理解信息可视化过程。 * 应用信息可视化技术。 * 设计信息可视化方法。 **课程价值：** 为了更有效地理解数据的敏感性，掌握有效的信息可视化方法至关重要。本课程鼓励学生和从业者学习，以开发更有效、更直观的可视化方法。
Data is growing tremendously on daily basis and visual representation is crucial to understand this growing data. The perceptive power of the human eye makes it easy for humans to understand complex phenomena. A visual representation should be easy to understand and easy to communicate with people. Visualizations help you explore hidden information in big data and are more reliable than statistical insights. Visualization helps people plan more effectively and interactively.Due to huge scope of visualization in data science and related fields, this course is designed for students with various backgrounds including computer science, engineering, mathematics, economics, and business schools.Our objective is to cover all main topics in this course such as motivation and purpose of information visualization, information visualization by examples, data representation, data description, data types, dataset types, attribute types, charts, visual encoding, information visualization with color, visualization process, human perception, analysis by example, interaction, visualization pipeline and techniques, design visual user interfaces, validation in information visualization, visualizing geographical data, visualizing networks and trees.This course helps students to able to learn the concepts of information visualization, understanding of information visualization process, application of information visualization, design of information visualization methods, and so on.To understand sensitivity of data, effective visualization methods are essential. Therefore, I would like to urge you all students and practitioners to take this course in order to develop more effective and intuitive visualization methods.
