FI:IV003 Algorithms II - Course Information
IV003 Algorithms and data structures II
Faculty of InformaticsSpring 2019
- Extent and Intensity
- 2/2. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Tomáš Effenberger, Ph.D. (seminar tutor)
Mgr. Jan Horáček (seminar tutor)
RNDr. Jan Mrázek (seminar tutor)
RNDr. Samuel Pastva, Ph.D. (seminar tutor)
RNDr. Martin Jonáš, Ph.D. (assistant)
RNDr. David Klaška (assistant) - Guaranteed by
- prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics
Supplier department: Department of Computer Science – Faculty of Informatics - Timetable
- Wed 20. 2. to Wed 15. 5. Wed 12:00–13:50 D2
- Timetable of Seminar Groups:
IV003/01: Thu 21. 2. to Thu 16. 5. Thu 14:00–15:50 B410, T. Effenberger, J. Horáček
IV003/02: Thu 21. 2. to Thu 16. 5. Thu 16:00–17:50 A217, S. Pastva
IV003/03: Thu 21. 2. to Thu 16. 5. Thu 10:00–11:50 A318, S. Pastva
IV003/04: Wed 18:00–19:50 B410, J. Mrázek - Prerequisites
- ( IB002 Algorithms I || PROGRAM(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 / plans the course is directly associated with
- Applied Informatics (programme FI, B-AP)
- Bioinformatics (programme FI, B-AP)
- Informatics with another discipline (programme FI, B-EB)
- Informatics with another discipline (programme FI, B-FY)
- Informatics with another discipline (programme FI, B-IO)
- Informatics with another discipline (programme FI, B-MA)
- Informatics with another discipline (programme FI, B-TV)
- Public Administration Informatics (programme FI, B-AP)
- Mathematical Informatics (programme FI, B-IN)
- Parallel and Distributed Systems (programme FI, B-IN)
- Computer Graphics and Image Processing (programme FI, B-IN)
- Computer Networks and Communication (programme FI, B-IN)
- Computer Systems and Data Processing (programme FI, B-IN)
- Programmable Technical Structures (programme FI, B-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (programme FI, N-AP)
- Social Informatics (programme FI, B-AP)
- Artificial Intelligence and Natural Language Processing (programme FI, B-IN)
- 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. - Syllabus
- 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.
- Literature
- required literature
- KLEINBERG, Jon and Éva TARDOS. Algorithm design. Boston: Pearson/Addison-Wesley, 2006, xxiii, 838. ISBN 0321372913. URL 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 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
- Czech
- Follow-Up Courses
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
General note: Předmět byl dříve vypisován pod kódem IB108. - Teacher's information
- https://is.muni.cz/auth/el/1433/jaro2018/IV003/index.qwarp
- Enrolment Statistics (Spring 2019, recent)
- Permalink: https://is.muni.cz/course/fi/spring2019/IV003