The Computing School will cover aspects that are relevant to all fields of crystallographic computing. As the main topic we will focus on the determination and the use of eigenvectors and eigenvalues and their applications in the different fields of crystallography. Applications range from the well known principal component analysis and other statistical and machine learning techniques to modelling using Markov processes, or optimization of functions. Fields such as image processing, information theory, and crystallography make use of these in many of its most fundamental methods. It impacts directly macromolecular crystallography in both phasing and refinement aspects. In small molecule crystallography and materials science research, it allows the understanding of very fundamental physical properties of matter. In this school, our aim is to learn and teach about this general topic from the computing aspect of the fundamentals, but also the computing tools and the data.