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Project-based course that explores computational algorithms to solve a selection of physics problems. Algorithmic methods include Monte Carlo, numerical integration, machine learning, and simulation of dynamical systems. Topics will be selected from application areas that include chaos, orbital motion, particle physics, quantum computation, climate and fluid dynamics. Course Information: No prior programming experience is required. Approved for both Letter and S/U grading. Prerequisite: Concurrent enrollment in PHYS 225.