What you'll learn
concepts of information visualization
understanding of information visualization process
application of information visualization
design of information visualization methods
Requirements
Need some common sense only...
Description
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.
Overview
Section 1: Lectures
Lecture 1 Introduction
Lecture 2 Visualization by Examples
Lecture 3 Information Visualization Process
Lecture 4 Data in Information Visualization
Lecture 5 Representation
Lecture 6 Fundamental Charts
Lecture 7 Visual Encoding 1
Lecture 8 Visual Encoding 2 and Validation
Lecture 9 Visualizing Data with Color
Lecture 10 Interaction and Visualization Guidelines
Lecture 11 Visualizing Geographical Data and Visualizing Networks and Trees
students are welcome from any domain or interest such as digital media, data science, data mining, data visualization, information visualization, economics, business schools.


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