In this course you will take 5 Steps to Good Data Science Practice in R: Version control with git: never lose a file or parts of an analysis again Reproducible computing with R: unit test your functions for full quality control Questionable research practices: avoid p-hacking, HARKING and Co. Good statistical practice: use correct p-values, sample size planning and multiple testing Tools in R for meta data: benefit from the power of metadata to reproduce research results You will acquire the necessary skills to make collaborative, reusable and transparent research, or in other words Open and Reproducible Science, too easy not to do.