Course detail

Data Structures and Algorithms

FEKT-MPC-PDAAcad. year: 2023/2024

Complexity theory, graph theory, graph equivalence, queuing theory, Petri nets, simulation and modeling, Markov models, advanced evolutionary algorithms.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Ing. Radim Burget, Ph.D.

Department

Department of Telecommunications (UTKO)

Entry knowledge

The subject knowledge on the heoretical informatics, t Bachelor degree and courlevel is required.

Rules for evaluation and completion of the course

final examination
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Aims

Objective of this course is to provide information about complexity theeory, graph theory and their comparison, queuing theory, Petri nets, evolution algorithms.
Alumni know complexity theory, representative examples and are able to apply graph theory, queue theory, theory of Petri nets and Markov models to solve the selected examples.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Virius, Miroslav. Základy algoritmizace. Česká technika-nakladatelství ČVUT, 2008. (CS)
GOODFELLOW, I., BENGIO, Y., & COURVILLEe, A. (2016). Deep learning (adaptive computation and machine learning series). Adaptive Computation and Machine Learning series, 800. (EN)