FI:IB002 Algorithms I - Course Information
IB002 Algorithms and data structures I
Faculty of InformaticsSpring 2021
- Extent and Intensity
- 2/2/1. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ivana Černá, CSc. (lecturer)
Mgr. Jakub Balabán (seminar tutor)
prof. RNDr. Jiří Barnat, Ph.D. (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
Bc. Andrej Čermák (seminar tutor)
Bc. Matej Focko (seminar tutor)
Mgr. Jan Horáček (seminar tutor)
Mgr. Nastasia Juračková (seminar tutor)
Mgr. Jan Koniarik (seminar tutor)
doc. Mgr. Jan Obdržálek, PhD. (seminar tutor)
Bc. Matěj Pavlík (seminar tutor)
RNDr. Jaromír Plhák, Ph.D. (seminar tutor)
doc. RNDr. Vojtěch Řehák, Ph.D. (seminar tutor)
Bc. Michal Staník (seminar tutor)
Bc. Jakub Šárník (seminar tutor)
Mgr. Mária Švidroňová (seminar tutor)
Mgr. Matěj Žáček (seminar tutor)
Mgr. Lukáš Korenčik (assistant)
Mgr. Martin Kurečka (assistant)
RNDr. Henrich Lauko, Ph.D. (assistant)
RNDr. Vladimír Štill, Ph.D. (assistant)
Hana Válková (assistant)
Mgr. Tatiana Zbončáková (assistant) - Guaranteed by
- prof. RNDr. Ivana Černá, CSc.
Department of Computer Science – Faculty of Informatics
Supplier department: Department of Computer Science – Faculty of Informatics - Timetable
- Wed 12:00–13:50 Virtuální místnost
- Timetable of Seminar Groups:
IB002/Konzultace02: Wed 10:00–11:50 Virtuální místnost, J. Horáček
IB002/01: Mon 10:00–11:50 Virtuální místnost, V. Řehák
IB002/02: Mon 14:00–15:50 Virtuální místnost, V. Řehák
IB002/03: Mon 16:00–17:50 Virtuální místnost, N. Beneš
IB002/04: Mon 16:00–17:50 Virtuální místnost, A. Čermák
IB002/05: Tue 8:00–9:50 Virtuální místnost, J. Obdržálek
IB002/06: Tue 10:00–11:50 Virtuální místnost, J. Obdržálek
IB002/07: Tue 10:00–11:50 Virtuální místnost, M. Staník
IB002/08: Tue 12:00–13:50 Virtuální místnost, J. Balabán
IB002/09: Tue 14:00–15:50 Virtuální místnost, M. Pavlík
IB002/10: Tue 16:00–17:50 Virtuální místnost, M. Švidroňová
IB002/101: No timetable has been entered into IS.
IB002/102: No timetable has been entered into IS.
IB002/103: No timetable has been entered into IS.
IB002/104: No timetable has been entered into IS.
IB002/105: No timetable has been entered into IS.
IB002/106: No timetable has been entered into IS.
IB002/107: No timetable has been entered into IS.
IB002/108: No timetable has been entered into IS.
IB002/109: No timetable has been entered into IS.
IB002/11: Wed 8:00–9:50 Virtuální místnost, M. Focko
IB002/110: No timetable has been entered into IS.
IB002/111: No timetable has been entered into IS.
IB002/112: No timetable has been entered into IS.
IB002/113: No timetable has been entered into IS.
IB002/114: No timetable has been entered into IS.
IB002/115: No timetable has been entered into IS.
IB002/116: No timetable has been entered into IS.
IB002/117: No timetable has been entered into IS.
IB002/118: No timetable has been entered into IS.
IB002/119: No timetable has been entered into IS.
IB002/12: Wed 16:00–17:50 Virtuální místnost, N. Beneš
IB002/120: No timetable has been entered into IS.
IB002/13: Wed 16:00–17:50 Virtuální místnost, M. Švidroňová
IB002/14: Thu 10:00–11:50 Virtuální místnost, J. Barnat
IB002/15: Thu 10:00–11:50 Virtuální místnost, J. Plhák
IB002/16: Thu 14:00–15:50 Virtuální místnost, V. Řehák
IB002/17: Thu 14:00–15:50 Virtuální místnost, J. Šárník
IB002/18: Thu 18:00–19:50 Virtuální místnost, N. Juračková, J. Koniarik
IB002/19: Fri 10:00–11:50 Virtuální místnost, J. Plhák
IB002/20: Fri 12:00–13:50 Virtuální místnost, M. Pavlík - Prerequisites
- IB001 Intro to Prog. using C || IB111 Foundations of Programming || IB999 Programming Test
The students should comprehend the basic notions on the level of IB111 Introduction to Programming and IB000 Mathematical Foundations of Computer Science Students should be able to: understand and apply basic constructs of programming languages (e.g., conditions, loops, functions, basic data types) in Python, know principles of recursion, and several basic algorithms. Students should know the basic mathematical notions; understand the logical structure of mathematical statements and mathematical proofs, specially mathematical induction; know discrete mathematical structures such as finite sets, relations, functions, and graph including their applications in informatics. - 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 58 fields of study the course is directly associated with, display
- Course objectives
- The course presents basic techniques of the analysis of algorithms, data structures, and operations. Students should correctly apply the basic data structures and algorithms as well as apply the algorithm design and analysis techniques when designing new algorithms. Students implement their algorithms in programming language Python.
- Learning outcomes
- After enrolling the course students are able to:
- actively use and modify basic sorting algorithms and graph algorithms,
- actively used basic techniques for designing algorithms (divide et impera, recursion) and design simple algorithms,
- actively used and modify basic static and dynamic data structures,
- employ time complexity and correctness of algorithms,
- analyze time complexity and prove the correctness of simple iterative and recursive algorithms,
- implement algorithms in the selected programming language (Python). - Syllabus
- Basic analysis of algorithms: The correctness of algorithms, input and output conditions, partial correctness, convergence, verification.
- Length of computation, algorithm complexity, problem complexity. Asymptotical analysis of time and space complexity, growth of functions.
- Algorithm design techniques. Divide et impera and recursive algorithms.
- Fundamental data structures: lists, queues. Representation of sets, hash tables. Binary heaps. Binary search trees, balanced trees (B trees, Red-black trees).
- Sorting algorithms: quicksort, mergesort, heapsort, lower bound for the time complexity of sorting.
- Graphs and their representation. Graph search. Depth-first traversal, topological sort, strongly connected components. Breadth-first traversal, bipartite graphs. Shortest paths, algorithm Bellman-Ford, Dijkstra's algorithm.
- Literature
- required literature
- CORMEN, Thomas H. Introduction to algorithms. 3rd ed. Cambridge, Mass.: MIT Press, 2009, xix, 1292. ISBN 9780262533058. URL info
- recommended literature
- SKIENA, Steven S. The algorithm design manual. New York: Springer, 1998, xvi, 486. ISBN 0387948600. info
- Teaching methods
- The course is organized as a series of lectures accompanied by exercises.
- Assessment methods
- The evaluation consists of written final exam and written exams during the term. Details can be found in learning materials https://is.muni.cz/auth/el/1433/jaro2021/IB002/index.qwarp
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- IB114 Introduction to Programming and Algorithms II
(IB111 || IB113) && !IB002 && !NOW(IB002) - IV003 Algorithms and Data Structures II
IB002 || program(PřF:N-MA) - IV100 Parallel and distributed computations
IB002 - MA015 Graph Algorithms
IB002||(typ_studia(N)&&fakulta(fi))
- IB114 Introduction to Programming and Algorithms II
- Teacher's information
- https://is.muni.cz/auth/el/1433/jaro2021/IB002/index.qwarp
- Enrolment Statistics (Spring 2021, recent)
- Permalink: https://is.muni.cz/course/fi/spring2021/IB002