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FP-NUMAcad. year: 2025/2026
Students will become familiar with the analysis of basic problems of numerical mathematics and suitable algorithms for their solution. The introductory part of the course is intended for familiarization with algorithm designs, data abstraction and their implementation so that students think about the use of computing resources algorithmically and thus be able to effectively use program resources for data processing in the future.Subsequently, the student will be introduced to some numerical methods (approximation of functions, solution of nonlinear equations, approximate determination of derivative and integral, solution of differential equations) suitable for modeling various problems of economic practice.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Rules for evaluation and completion of the course
Credit requirements:
Passing two control tests and achieving at least 55% of the points. In case of absence, it is possible to complete one of the assignments in the credit week. One of the written assignments can be corrected during the credit week.Awarding credit is a necessary condition for taking the exam.
The exam is written and lasts 1 hour. If the student does not achieve at least 50% of the total number of attainable points, the entire exam are graded "F" (at ECTS).
Individual study plan:Credit requirements:Passing the comprehensive control test and achieving at least 55% of the points.
Participation in exercises is controlled.
Aims
Understand the general principles and types of computational methods, along with the issues of their convergence and stability. Know the sources of errors, their classification, and perform error estimation. Master effective approximate methods for solving algebraic and transcendental equations, systems of linear and nonlinear equations, basic methods of function approximation, approximate methods for calculating definite integrals, and Monte Carlo methods for selected problems.
Study aids
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Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
Lecture
Teacher / Lecturer
Syllabus
1. The concept of an algorithm and the complexity of an algorithm (algorithm, basic properties, flowchart, cycles with a constant number of repetitions, with a condition at the beginning and end of the cycle)2. Characterization of calculation methods, errors and their classification, convergence and stability, repetition of the course of the function,3. Solving nonlinear equations4. Solving linear systems5. Roots of polynomials, use of Horner's scheme6. Interpolation, summary of the material discussed7. Approximation of functions8. Numerical integration and derivation9. Numerical solution of differential equations10. Graphs (undirected, directed and evaluated, Dijkstra's shortest path algorithm, Kruskal's algorithm)11. Differential equation12. Monte Carlo methods, summary of the material discussed13. Application of numerical methods in practice
Exercise