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Course overview

From dashboards to cutting-edge scientific papers, from a home office to the largest companies in the world, we extensively use data visualization to reveal patterns in data. As our world becomes increasingly connected and digitized, and as decisions are increasingly driven by data, data visualization is becoming a critical skill for every knowledge worker. This course is an introduction to basic statistical data analysis and visualization. We will learn fundamentals of data visualization, in the context of visual perception, integrity, design, and statistics, as well as various types of data and visualization techniques. The hands-on exercises using Python stack and D3.js will be an integral part of the course.

Course objectives

By the end of the course, you are expected to understand, explain, and handle basic types of data, analyze them using basic exploratory visualization techniques, and create explanatory web-based visualizations. You will also be able to evaluate the effectiveness of data visualizations based on the principles of human perception, design, types of data, and visualization techniques.

Basic Information

  • Homepage: https://yy.github.io/dviz-course/
  • GitHub: https://github.com/yy/dviz-course
  • Instructor: Yong-Yeol (YY) Ahn (Office Hours: Wed 9-10am)
  • Relationships with S637 Information Visualization (IVMOOC): Compared with S637, this course is more geared towards fundamental statistical visualizations and exploratory data analysis, using Python stack and D3.js. Therefore, this course may be suitable for students who pursue their careers in research, developement, data analysis, and so on.
  • Announcements: All announcements will be sent via Canvas and Slack.
  • Prerequisites: This course is open to advanced undergraduate students (I422) as well as graduate students (I590). Because programming (in Python and Javascript) is an integral part of the course, it is required to have good understanding and working knowledge of programming. The basic programming courses (Both I210/I211 or equivalent) are required prerequisites. In addition, I308: Information Representation and a basic statistics course is a recommended prerequisite. Basic understanding of design process and web (HTML, CSS, Javascript) is also highly recommended.
  • Syllabus: You can download the syllabus here, but you should check this homepage for up-to-date information.

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Special Thanks