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This lecture covers the objectives of mastering state-of-the-art methods in continuous optimization and simulation, understanding theoretical foundations, learning statistical techniques, and using simulation for complex optimization problems. Topics include drawing from distributions, the Poisson process, discrete events simulation, statistical analysis, bootstrapping, variance reduction, and simulation projects. Practical information includes live Zoom lectures and exercises, with a focus on simulation and optimization projects. The course also involves an exam, project presentations, and group work evaluation. The slides discuss modeling, causal effects, uncertainty, simulation, and the importance of looking beyond the mean in simulation studies.