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An introduction to the phenomenology of nonlinear dynamic behavior with emphasis on models of actual physical, chemical, and biological systems, involving an interdisciplinary approach to ideas from mathematics, computing, and modeling. The common features of the development of chaotic behavior in both mathematical models and experimental studies are stressed, and the use of modern data-mining tools to analyze dynamic data will be explored. Emphasis will be placed on the geometric/visual computer-aided description and understanding of dynamics and chaos. Prerequisite(s): Knowledge of linear algebra and ordinary differential equations (at an undergraduate level); some computing experience is desirable.