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1. Introduction and general overview.
2. Approximation Theory. The Fast Fourier transform.
3. Methods for solving systems of linear and nonlinear equations. Gauss elimination, pivoting. Cholesky factorisation. Conditioning and error analysis. Least squares solution, Schur decomposition, the QR and QZ algorithms. Iterative methods: Jacobi, Gauss-Seidel, SOR.
The Conjugate Gradient Method. Krylov subspace methods: Arnoldi algorithm. Conjugate gradient method and GMRES.
4. Numerical methods for ODEs. Taylor series methods. Runge-Kutta methods. Multi-step methods.
Boundary value problems: shooting methods, finite difference methods, collocation. Methods for conservative and stiff problems.
5. Numerical methods for PDEs. Finite difference methods for elliptic equations. Parabolic equations: explicit, implicit and the Crank-Nicolson methods. The Galerkin, finite element and spectral methods.