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

7

Mode of study

Not applicable.

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

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

Recommended reading

Not applicable.

Elearning

Classification of course in study plans

  • Programme MPC-IBE Master's 1 year of study, winter semester, compulsory

  • Programme MPC-AUD Master's

    specialization AUDM-TECH , 2 year of study, winter semester, compulsory-optional

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Syllabus

Teorie složitosti, teorie grafů, ekvivalence grafů, teorie hromadné obasluhy, Petriho sítě a modelování pomocí Petriho sítí, Markovovy modely, pokročilé evoluční algoritmy.

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

Syllabus

Teorie složitosti, teorie grafů, ekvivalence grafů, teorie hromadné obasluhy, Petriho sítě a modelování pomocí Petriho sítí, Markovovy modely, pokročilé evoluční algoritmy.

Project

13 hod., compulsory

Teacher / Lecturer

Syllabus

Vybrané metody pro optimalizaci ExpSpace problému.

Elearning