Data Analysis and Visualization in Python
Course further information
This workshop gives you a practical introduction to the basics of Python. It requires no prior experience with programming.
Code is everywhere - and scientific research is no exception to this. Programming allows researchers to handle large amounts of digital data with ease, to automate tasks that would otherwise be time-consuming or even impossible to do, and to explore new approaches. Programming skills allow you to be more autonomous of pre-existing tools and to tailor your workflow to your own needs.
Python is one of the world's most popular programming languages, not only but also, for scientific programming. Part of its popularity comes from the fact that is rather easy to learn. But most importantly, you can use Python for a broad range of tasks, e.g. text analysis, sequence analysis, mathematical computations, machine learning, visualization, and many more.
This workshop gives you a practical introduction to the basics of Python. It requires no prior experience with programming. Our goal is to show you some of the potential of Python, help you get started with programming and prepare you to take your next steps (on your own or in another course).
