Dates: online, 17th-20th October
n this course we’ll learn how to organize a data-visualization project, from initial data cleanup and preparation to actual visualization. We’ll cover best (and worst) practices, and we’ll see many self contained exercises that will familiarize the student with different plot types, from classical line and bar charts, to maps, networks and subplots.
The course is aimed at students, researchers and professionals interested in improving their data visualization skills. While science-oriented problems are the most common application, any field that produces data could be fertile ground for data visualization.
Some familiarity with Python is required, but attendants are not expected to be masters. If you want to improve your Python skills in preparation for the course, please have a look at these exercise: https://github.com/ne1s0n/bioinformateachers/tree/main/python_exercises