FI:IB108 Algorithm Design II - Course Information
IB108 Algorithm Design IIFaculty of Informatics
- Extent and Intensity
- 2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Petra Budíková, Ph.D. (seminar tutor)
RNDr. Jana Tůmová, Ph.D. (seminar tutor)
Bc. Filip Bártek (assistant)
Mgr. Petr Bauch, Ph.D. (assistant)
RNDr. Nikola Beneš, Ph.D. (assistant)
Mgr. Sven Dražan (assistant)
RNDr. Mgr. Jana Dražanová (assistant)
Mgr. Jan Láník (assistant)
RNDr. Jan Papoušek, Ph.D. (assistant)
Mgr. Adam Streck (assistant)
- Guaranteed by
- prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science - Faculty of Informatics
- Mon 12:00–13:50 D2
- Timetable of Seminar Groups:
IB108/02: each odd Tuesday 8:00–9:50 B410, P. Budíková
IB108/03: each even Thursday 18:00–19:50 B410, J. Tůmová
IB108/04: each odd Thursday 18:00–19:50 B410, J. Tůmová
- Prerequisites (in Czech)
- IB002 Algorithms I
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 17 fields of study the course is directly associated with, display
- Course objectives
- The course expands on the introductory course Algortihm Design I. It presents algorithmic concepts without their direct connection to any particular programming language. The aim is to introduce students into design and analysis of advanced algorithms. The course presents advanced techniques of algorithm analysis and a wide spectrum of strategies together with algorithms built up on these strategies. Students are introduced into new data structures which are displayed in a row with algorithms based on them.
- Advanced design and analysis techniques: dynamic programming, greedy strategies,backtracking. Amortized analysis.
- Advanced data structures: binomial and Fibonacci heaps, data structures for disjoint sets.
- Graph algorithms: Single-Source Shortest Paths (The Bellman-Ford algorithm). All-Pairs Shortest Paths (Shortest paths and matrix multiplication, The Floyd-Warshall algorithm, Johnson's algorithm for sparse graphs). Maximum Flow (The Ford-Fulkerson method, The Push-Relabel method). Maximum bipartite matching.
- String matching: the naive string-matching algorithm, Karp-Rabin algorithm, string matching with finite automata. The Knuth-Morris-Pratt algorithm.
- DASGUPTA, Sanjoy, Christos Ch. PAPADIMITRIOU and Umesh Virkumar VAZIRANI. Algorithms. 1st ed. Boston: McGraw-Hill Companies, 2008. x, 320. ISBN 9780073523408. info
- KLEINBERG, Jon and Éva TARDOS. Algorithm design. Boston: Pearson/Addison-Wesley, 2006. xxiii, 838. ISBN 0321372913. info
- CORMEN, Thomas H., Charles Eric LEISERSON and Ronald L. RIVEST. Introduction to algorithms. Cambridge: MIT Press, 1989. xvii, 1028. ISBN 0070131430. info
- Teaching methods
- Lectures and seminars. Students are required to solve given algorithmical problems.
- Assessment methods
- The course has a form of a lecture with a seminar. During the term students separately solve sets of algorithmic problems. The course is concluded by the written exam. Student can attend the final exam providing she/he has acquired given number of points from problem sets.
- Language of instruction
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
- Listed among pre-requisites of other courses
- Teacher's information