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The course covers the basic principles of creating efficient algorithms, data structures and graph theory that every computing expert should know.
Last update: Svozil Daniel (04.01.2019)
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Students will be able to:
Last update: Kubová Petra (02.01.2018)
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Pro zı́skánı́ zápočtu je potřeba dostatek bodů ze semestrálního testu a z programovacích úloh. Zkouška se skládá z povinné pı́semné části a z volitelné ústnı́ části. Last update: Svozil Daniel (07.02.2018)
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R:Cormen, T. H., Leiserson, C. E., Rivest, R. L. Introduction to Algorithms. The MIT Press, 2001. ISBN 0262032937. R:Handbook of Graph Theory, 2nd Edition (Discrete Mathematics and Its Applications). Chapman and Hall/CRC, 2013. ISBN 978-1439880180. Last update: Kubová Petra (02.01.2018)
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1. Motivation and introduction to graph theory 2. Basic definitions and concepts of graph theory I 3. Basic definitions and concepts of graph theory II 4. Sorting algorithms O(n^2). Binary heaps and HeapSort. 5. Dynamic fields, amortized complexity, binomial heaps 6. Search trees and their balancing 7. Probabilistic algorithms and their complexity. QuickSort. 8. Recursive algorithms and divide and conquer. Linear sorting 9. Hashing and searching tables 10. Dynamic programming 11. Graph minimum spanning tree 12. Shortest paths in graphs 13. Reserve Last update: Svozil Daniel (04.01.2019)
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An ability to solve basic algorithmic problems actively, to express the algorithmic solution in a high-level programming language (Java, C++), and knowledge of basic notions from calculus and combinatorics is assumed. Last update: Kubová Petra (02.01.2018)
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Teaching methods | ||||
Activity | Credits | Hours | ||
Konzultace s vyučujícími | 1 | 28 | ||
Účast na přednáškách | 1 | 28 | ||
Práce na individuálním projektu | 2 | 56 | ||
Příprava na zkoušku a její absolvování | 1 | 28 | ||
Účast na seminářích | 1 | 28 | ||
6 / 6 | 168 / 168 |