1. Errors in numerical calculations. Linear spaces and operators, fixed point theorems. Iterative methods for the analysis of nonlinear algebraic and selected further equations. 2. Iterative and coupled methods for the analysis of linear algebraic equations, relaxation methods, method of conjugated gradients. 3. Multiplicative decomposition of matrices. Numerical evaluation of eigenvalues and eigenvectors of matrices and of inverse matrices, algorithms for special matrices. 4. Condition numbers of systems of linear equations. Least squares method, pseudoinverse matrices. 5. Generalizations of methods from 3. and 4. to the analysis of systems of nonlinear equations. 6. Lagrange and Hermite interpolation of functions of 1 variable, namely polynoms and splines. 7. Approximation of functions of 1 variable using the least squares methos: linear and nonlinear approach. 8. Approximation of function of more variables. 9. Numerical differentiation. Finite difference method for the analysis of selected initial and boundary problems for ordinary differential equations. 10. Numerical quadrature. Finite element method for the analysis of selected initial and boundary problems for ordinary differential equations. 11. Time-dependent problems. Time discretization: Euler methods, Cranka-Nicholson method, Runge-Kutta methods, Newmark method. 12. Generalization of 9. and 10. for pro partial differential equations of evolution, e.g. heat transfer equations, fluid flow equations and equations of dynamics of building structures. 13. Sensitivity and inverse problems. Identification of uncertain material parameters from known measurement results. Selected engineering application, due to other courses.

Seminars follow the related lectures: 1. Errors in numerical calculations. Linear spaces and operators, fixed point theorems. Iterative methods for the analysis of nonlinear algebraic and selected further equations. 2. Iterative and coupled methods for the analysis of linear algebraic equations, relaxation methods, method of conjugated gradients. 3. Multiplicative decomposition of matrices. Numerical evaluation of eigenvalues and eigenvectors of matrices and of inverse matrices, algorithms for special matrices. 4. Condition numbers of systems of linear equations. Least squares method, pseudoinverse matrices. 5. Generalizations of methods from 3. and 4. to the analysis of systems of nonlinear equations. 6. Lagrange and Hermite interpolation of functions of 1 variable, namely polynoms and splines. 7. Approximation of functions of 1 variable using the least squares methos: linear and nonlinear approach. 8. Approximation of function of more variables. 9. Numerical differentiation. Finite difference method for the analysis of selected initial and boundary problems for ordinary differential equations. 10. Numerical quadrature. Finite element method for the analysis of selected initial and boundary problems for ordinary differential equations. 11. Time-dependent problems. Time discretization: Euler methods, Cranka-Nicholson method, Runge-Kutta methods, Newmark method. 12. Generalization of 9. and 10. for pro partial differential equations of evolution, e.g. heat transfer equations, fluid flow equations and equations of dynamics of building structures. 13. Sensitivity and inverse problems. Identification of uncertain material parameters from known measurement results. Selected engineering application, due to other courses.