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Lecturer(s)
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Hradil Pavel, Ing.
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Černá Lucie, prof. Dr. Ing.
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Kajaba František, Ing.
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Course content
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- Algorithmics from a practical point of view, algorithmical complexity in a practical use - Brute force, greedy algorithm, incremental algorithms - Geometric algorithms - Amusing algorithms - Randomized algorithms - Clustering - Data stream algorithms - In-place and in situ algorithms - Quantum computing
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Learning activities and teaching methods
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Interactive lecture, Project-based instruction, Multimedia supported teaching, Students' portfolio, Task-based study method, Individual study, Students' self-study, Self-study of literature, Practicum
- Contact hours
- 52 hours per semester
- Individual project (40)
- 40 hours per semester
- Presentation preparation (report) (1-10)
- 5 hours per semester
- Preparation for an examination (30-60)
- 40 hours per semester
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| prerequisite |
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| Knowledge |
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| samostatně vytvořit jednoduchý algoritmus |
| využívat v algoritmizaci datové struktury pole, seznam, strom |
| Skills |
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| programovat v jazyce Java nebo C nebo C++ nebo C# nebo Pascal/Delphi |
| samostatně studovat odbornou literaturu z oblasti informatiky |
| Competences |
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| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| - fundamental algorithmic strategies andtheir use to solve a particular problem with a particular type of data, |
| - knowledge of further modern methods, such as randomized, data stream and in-place algorithms, |
| - brief information about news and trends in the area of algorithmics, |
| Skills |
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| - design of algorithms to solve particular problems. |
| - evaluation of suitability of an algorithm for a given problem |
| - understanding and shortened survey of a computer science text |
| - analysis of a simpler programming work with documentation |
| Competences |
|---|
| N/A |
| N/A |
| N/A |
| teaching methods |
|---|
| Knowledge |
|---|
| Lecture |
| Task-based study method |
| Individual study |
| Students' portfolio |
| Textual studies |
| Skills |
|---|
| Practicum |
| Task-based study method |
| Students' portfolio |
| Individual study |
| assessment methods |
|---|
| Knowledge |
|---|
| Written exam |
| Oral exam |
| Project |
| Individual presentation at a seminar |
| Skills |
|---|
| Project |
| Individual presentation at a seminar |
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Recommended literature
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Dvořák, Stanislav. Dekompozice a rekursivní algoritmy. Praha: Grada, 1992. ISBN 80-85424-76-2.
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Gonnet, Gaston H.; Baeza-Yates, R. Handbook of algorithms and data structures : in Pascal and C. Wokingham: Addison-Wesley, ----. ISBN 0-201-41607-7.
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Hromkovič, Juraj. Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics. 2nd ed. Berlin: Springer, 2003. ISBN 3-540-44134-4.
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Michalewicz, Z.; Fogel, D.B. How to solve it: Modern Heuristics. Springer: Verlag, 2000.
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Moret, Bernard M. E.; Shapiro, H. D. Algorithms from P to NP. Vol. 1, Design & efficiency. Redwood City: Benjamin/Cummings Publishing, 1991. ISBN 0-8053-8008-6.
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Rawlins, Gregory J. E. Compared to what? : an introduction to the analysis of algorithms. New York: Computer Science Press, 1992. ISBN 0-7167-8243-X.
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Skiena, Steven S. The algorithm design manual. New York: Springer, 1998. ISBN 0-387-94860-0.
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