To enable students to develop abstract thinking and gain basic knowledge of numerical mathematics and optimization methods.

The acquired knowledge is used for further education and in vocational courses for making and solving real mathematical models within vocational courses, using the practiced material in numerical mathematics and optimization methods.

Theoretical teaching (lectures): Module: Numerical mathematics. Approximate numbers. Function approximations. Numerical solving nonlinear equations. Systems of nonlinear equations. Monte-Carlo method. Module: Optimization. Classical optimization. One-dimension optimization methods. Linear programming (graphical method, simplex method; transport problem). Mathematical method and simulation. Practical course (exercises): Appropriate examples from theoretical background are done during exercises, thus practicing a given material, and in such a way the exercises are contributing to understanding of a given material.

Lectures, Numerical-calculation and laboratory (computer) exercises. Consultation. Lectures are conducted in combination. The lecture of theoretical part is followed by examples which serve to clarify the theoretical part of the curriculum. During computational exercises, which follow the lectures, some typical tasks are done, which deepens the exposed material from the lectures, and the laboratory (computer) use of software packages (at least one) e.g.: C, Maple, Mathematica, Matlab. Apart from lectures and exercises, consultations are regularly held. Part of the material, which forms a logical whole, may be taken as an exam during the teaching process in the form of the following two parts (part one: Numerical Mathematics, Part II: Optimization). The oral part of the final exam is eliminatory.