|
Lecturer(s)
|
-
Vocke Jan, Ing.
-
Vejmělková Ivana, Prof. Dr. Ing.
|
|
Course content
|
1. Introduction into algorithms - correctness and efficacy of algorithms, robustness, analyses, problem solving 2.-6. Algorithmical strategies - brute force, greedy, incremental algorithms, divide & conquer, dynamic programmimg, backtracking 7. Randomized algorithms 8. Data stream algorithms 9. In-place and in situ algorithms 10. Heuristics and approximate solutions 11. Algorithmical complexity in real life 12. News and trends 13. Selected interesting "recreational" problems
|
|
Learning activities and teaching methods
|
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
|
| prerequisite |
|---|
| Knowledge |
|---|
| samostatně vytvořit jednoduchý algoritmus |
| využívat v algoritmizaci datové struktury pole, seznam, strom |
| Skills |
|---|
| programovat v jazyce Java nebo C nebo C++ nebo C# nebo Pascal/Delphi |
| samostatně studovat odbornou literaturu z oblasti informatiky |
| Competences |
|---|
| N/A |
| N/A |
| learning outcomes |
|---|
| Knowledge |
|---|
| - 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 |
|---|
| - 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 |
|
Recommended literature
|
-
Dvořák, Stanislav. Dekompozice a rekursivní algoritmy. Praha : Grada, 1992. ISBN 80-85424-76-2.
-
Gonnet, Gaston H.; Baeza-Yates, R. Handbook of algorithms and data structures : in Pascal and C. Wokingham : Addison-Wesley, ----. ISBN 0-201-41607-7.
-
Hromkovič, Juraj. Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics. 2nd ed. Berlin : Springer, 2003. ISBN 3-540-44134-4.
-
Michalewicz, Z.; Fogel, D.B. How to solve it: Modern Heuristics. Springer-Verlag, 2000.
-
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.
-
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.
-
Skiena, Steven S. The algorithm design manual. New York : Springer, 1998. ISBN 0-387-94860-0.
|