Because of the complexity inherent in biological systems, many researchers frequently rely on a combination of global analysis and computational approaches to gain insight into both (i) how interacting components can produce complex system behaviors, and (ii) how changes in conditions may alter these behaviors. Because the biological details of a particular system are generally not taught along with the quantitative approaches that enable hypothesis generation and analysis of the system, we developed a course at Mount Sinai School of Medicine that introduces first-year graduate students to these computational principles and approaches. We anticipate that such approaches will apply throughout the biomedical sciences and that courses such as the one described here will become a core requirement of many graduate programs in the biological and biomedical sciences.