Introduction to Computational Science and Engineering

CSE.0002x will teach you how to use to solve problems in engineering and science including simulation of time-dependent phenomena; optimization of systems; and quantification of uncertainty. This course is primarily for learners with some prior programming experience in Python and an introductory knowledge of calculus and mechanics (typical of a first-year college course in these topics). You will spend a considerable amount of time writing programs to implement the concepts covered in the course. For example, you will write programs that will: simulate the descent of a lander in the Martian atmosphere; optimize the placement of cellular towers on the MIT campus; and quantify the likelihood of significant climate temperature rise under different scenarios. Topics covered include: - Advanced programming in Python 3 and NumPy - Plotting with Matplotlib - Initial value problems - Discretization with explicit and implicit methods - Solution of linear and nonlinear systems of equations - Unconstrained optimization and gradient descent - Probability, distributions - Monte Carlo simulations - Confidence intervals

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