This course introduces participants to crisp set and fuzzy set Qualitative Comparative Analysis (QCA) and its analysis in R. It provides participants with a basic understanding of the analytic underpinnings and steps of QCA, and enables them to independently perform a basic crisp or fuzzy set QCA (Standard Analysis). We will look at the origins, analytic aims, and variants of QCA, and deal in depth with techniques and practices of set calibration. The nuts and bolts the QCA technique, from parameters of fit to all steps of the analyses of necessity and sufficiency, are illustrated based on an empirical example study which we replicate in class. We will then cover the presentation and interpretation of QCA results, as well as ways to deal with limited diversity and other potential pitfalls. Hands-on exercises and daily lab sessions provide opportunities for practice and engagement.