The development of research software has become an important part of research projects in many areas of science and engineering. At the same time, increasing computational power in the area of high performance computing has made computationally challenging statistical tasks feasible and highly desirable in many application fields.
In this week-long summer school, we will therefore address these different aspects and familiarize you with the most essential paradigms of software development, which support the design of efficient, user-friendly, and sustainable software. In particular, we will focus on the scientific programming language Julia.
The summer school is organized around keynote presentations by invited Julia experts and many hands-on tutorials. First, a gentle introduction including packaging, testing, virtualization, interaction, and visualization will supply you with the essential skills you need to use Julia in your research. Afterwards, we build on these skills to implement computationally expensive statistical methods. In particular, we will focus on methods for regression and resampling using bootstrap and permutations. That is, methods addressing two of the most common challenges in statistics: estimation of the relationship between variables of interest and the quantification of uncertainty. You are invited to bring your own problem to apply the skills you learn in this summer school.