This course introduces students to data-driven analysis, modeling and decision making for complex real systems based on discrete-event simulation. We mainly focus on problems that have no closed-form solutions but with abundant data resources. The course provides a solid mathematical/statistical grounding in simulation and some tools to solve actual problems. It will cover data collection and input data analysis, modeling techniques, random number generators, discrete-event simulation approaches, simulated output data analysis, simulation variance reduction techniques and state-of-the-art simulation software.