Classifying real-life problems and choosing the most appropriate numerical solution algorithms; algorithms implementation in MATLAB and Python
Course Prerequisites
Integral and differential calculus for real valued functions; complex numbers; linear algebra; programming
Teaching Methods
Class lectures and exercises, programming exercises
Assessment Methods
The exam will be written. Each student will be offered a couple of questions on topics developed in the classes and has one hour to answer
Texts
● Instructor slides ● For further reading: A. Quarteroni, R. Sacco, F. Saleri. Numerical Mathematics-2nd edition. Springer Series: Texts in Applied Mathematics, Vol. 37 (2007)
Contents
● Direct methods for solving linear systems ● Iterative methods for solving linear systems ● Approximation of eigenvalues and eigenvectors ● Solution of nonlinear systems ● Least-squares approximation ● Polynomial interpolation ● Numerical integration ● Numerical solution of ordinary differential equations
