Python and Anaconda support a variety of processes in the scientific data workflow, from getting data, manipulating and processing data, and visualizing and communicating research results. Because Python can be used in a wide variety of applications, even beyond scientific computing, users can avoid having to learn new software or programming languages when new data analysis needs arise. Python's open source availability enhances research reproducibility and enables users to connect with a large community of fellow users. Learning About Anaconda and Python • Quick start guide from Anaconda's website • Offered by Software Carpentry, this set of online tutorials provides a basic introduction to scientific computing with Python. • The tutorials on this page are aimed at people who have previous experience with other programming languages (C, Perl, Lisp, Visual Basic, etc).