Mathematical, numerical and computational techniques for practical problems involving optimization, simulation and approximation. The course emphasises the properties and implementation of numerical algorithms for solving linear, non-linear and differential equations, approximating data using interpolation, least squares, and splines. These fundamental methods have a wide variety of applications in science, ranging from solving physics problems by approximating integrals and derivatives, to digital image compression using singular-value decomposition.
Programming Language: Python
Libraries: NumPy, SciPy, and Matplotlib.
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