FI:IV003 Algorithms II - Course Information
IV003 Algorithms and Data Structures IIFaculty of Informatics
- Extent and Intensity
- 2/2. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Jaroslav Bendík (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
Mgr. Samuel Pastva (seminar tutor)
RNDr. František Blahoudek, Ph.D. (assistant)
RNDr. Martin Jonáš (assistant)
Mgr. David Klaška (assistant)
Bc. Tomáš Lamser (assistant)
- Guaranteed by
- prof. RNDr. Ivana Černá, CSc.
Department of Computer Science - Faculty of Informatics
Supplier department: Department of Computer Science - Faculty of Informatics
- ( IB002 Algorithms I || PROGRAM ( 1431:N - MA )) && ! IB108 Algorithms II
The course expands on courses IB002 Algorithms and Data Structures 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 the course is directly associated with
- there are 55 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.
- Learning outcomes
- After enrolling the course students are able to:
- actively use and modify advanced graph and string algorithms,
- actively used advanced techniques for designing algorithms (dynamic programming, greedy techniques) for designing algorithms, expain their specific properties and limits,
- actively used and modify advanced dynamic data structures and use them for designing effective algorithsm,
- analyze time complexity and prove correctness of algorithms.
- 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.
- required literature
- KLEINBERG, Jon and Éva TARDOS. Algorithm design. Boston: Pearson/Addison-Wesley, 2006. xxiii, 838. ISBN 0321372913. info
- recommended literature
- DASGUPTA, Sanjoy, Christos Ch. PAPADIMITRIOU and Umesh Virkumar VAZIRANI. Algorithms. 1st ed. Boston: McGraw-Hill Companies, 2008. x, 320. ISBN 9780073523408. info
- CORMEN, Thomas H., Charles E. 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 algorithmic 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. A 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 (probably available only in Czech)
- The course is taught annually.
The course is taught: every week.
General note: Předmět byl dříve vypisován pod kódem IB108.
- Teacher's information