Course overview
Course description
Data visualization plays a pivotal role in understanding information, from news articles to cutting-edge scientific research, and is employed across diverse settings, from home offices to the world's largest corporations. As an integral component of data analysis, data visualization has become a crucial skill for all knowledge workers.
This introductory course delves into the core concepts of statistical data analysis and visualization. You will explore the foundations of data visualization, covering topics such as perception, integrity, design principles, statistical methods, data classifications, and various visualization techniques. Through hands-on exercises utilizing the Python stack, students will develop practical skills in data processing and visualization.
Course objectives
Upon completing the course, you are expected to acquire the ability to produce data visualizations that are effective, accurate, and ethical. You will also be able to critically evaluate data visualizations and effectively communicate your findings to others. This ability will build on your understanding of the fundamental principles of data visualization, including human perception, design, data types, and visualization techniques. Your proficiency will be showcased through a course project through which you will not only create data visualizations but also document the process of creating effective, accurate, and ethical data visualizations.
Relationships with IVMOOC
This course differs from E583/Z637 in that it places greater emphasis on fundamental statistical visualizations and conducting exploratory data analysis through coding, utilizing the Python data science and visualization stack. As a result, it may be a more suitable choice for students aiming for careers in research, development, engineering, and data analysis, or for those who will directly handle and analyze complex datasets.
Basic Information
- Homepage: https://yyahn.com/dviz-course/
- GitHub: https://github.com/yy/dviz-course
- Instructor: Yong-Yeol (YY) Ahn (Office Hours: Check Canvas)
- 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.
Links
Special Thanks
- Francisco Alfaro helped the migration with mkdocs.