We enable students to become protean data scientists with eminently transferable skills. We provide students with a broad training in computational and theoretical techniques for (1) describing and understanding complex natural and sociotechnical systems, enabling them to then, as possible, (2) predict, control, manage, and create such systems. Major skill sets we want students at all levels to develop: Data wrangling: Methods of data acquisition, storage, manipulation, and curation. Visualization techniques, with a potential for building high quality web-based applications. Uncovering complex patterns and correlations in systems through data-fueled machine learning, and genetic programming. Powerful ways of identifying and extracting explanatory, mechanistic stories underlying complex systems—not just how to use black box techniques.

Students must have prior coursework or be able to establish competency in: Calculus, Coding (Python/R ideal but not necessary), Data structures, Linear algebra, Probability and Statistics.