This is a multi-level course website aspiring to cover various topics and with different aims. It is basically structured for students that may either at beginner or more advanced level in programming and data science with the focus being on biological applications. In this sense the presented material covers diverse topics that are centered on three main axes:
Mastering the material
Who can follow the material covered in each case?
In principal anyone with a basic (high-school) level of statistics can follow Data Analysis with R, in fact he/she is actually recommended to do so. The course starts from scratch and is structured as a step-by-step tutorial on the language.
Methods for Data Analysis require some background on basic algebra (the stress on "basic"). It is recommended for post-graduate students who have taken classes on bioinformatics, computational biology or something similar at undergraduate level, but it mostly requires a genuine interest in data analysis per se, that is if you are really motivated into making sense of your data you are expected to have no problem.
Post-graduates with a molecular biology background are expected to master the material covered in NGS Data Analysis with greater ease than students of other disciplines. A molecular biology primer at under- or post-graduate level is required to get you through this course. Students are also expected to have a certain familiarity with command line interphases (i.e. Linux or similar).