FI:IB002 Algorithms I - Course Information
IB002 Algorithms and data structures I
Faculty of InformaticsSpring 2025
- 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)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
Kateřina Borošová (seminar tutor)
Vojtěch Brdečko (seminar tutor)
Mgr. Tomáš Foltýnek, Ph.D. (seminar tutor)
Vojtěch Kůr (seminar tutor)
Mgr. Tomáš Macháček (seminar tutor)
RNDr. Vít Musil, Ph.D. (seminar tutor)
doc. Mgr. Jan Obdržálek, PhD. (seminar tutor)
RNDr. Jaromír Plhák, Ph.D. (seminar tutor)
doc. RNDr. Vojtěch Řehák, Ph.D. (seminar tutor)
Tereza Siková (seminar tutor)
Bc. Jakub Šárník (seminar tutor)
Mgr. Matěj Žáček (seminar tutor) - Guaranteed by
- prof. RNDr. Ivana Černá, CSc.
Department of Computer Science – Faculty of Informatics
Supplier department: Department of Computer Science – Faculty of Informatics - Prerequisites
- ( IB015 Non-Imperative Programming || IB111 Foundations of Programming ) && ! NOW ( IB114 Intro to Programming & Algs II )
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. IB114 is a similar course designed for a different curriculum. - 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
- Image Processing and Analysis (programme FI, N-VIZ)
- Bioinformatics and systems biology (programme FI, N-UIZD)
- Computer Games Development (programme FI, N-VIZ_A)
- Computer Graphics and Visualisation (programme FI, N-VIZ_A)
- Computer Networks and Communications (programme FI, N-PSKB_A)
- Cybersecurity Management (programme FI, N-RSSS_A)
- Formal analysis of computer systems (programme FI, N-TEI)
- Graphic design (programme FI, N-VIZ)
- Graphic Design (programme FI, N-VIZ_A)
- Hardware Systems (programme FI, N-PSKB_A)
- Hardware systems (programme FI, N-PSKB)
- Image Processing and Analysis (programme FI, N-VIZ_A)
- Information security (programme FI, N-PSKB)
- Informatics (programme FI, B-INF) (2)
- Informatics in education (programme FI, B-IVV) (2)
- Information Security (programme FI, N-PSKB_A)
- Quantum and Other Nonclassical Computational Models (programme FI, N-TEI)
- Computer graphics and visualisation (programme FI, N-VIZ)
- Computer Networks and Communications (programme FI, N-PSKB)
- Principles of programming languages (programme FI, N-TEI)
- Programming and development (programme FI, B-PVA)
- Cybersecurity management (programme FI, N-RSSS)
- Services development management (programme FI, N-RSSS)
- Software Systems Development Management (programme FI, N-RSSS)
- Services Development Management (programme FI, N-RSSS_A)
- Software Systems Development Management (programme FI, N-RSSS_A)
- Software Systems (programme FI, N-PSKB_A)
- Software systems (programme FI, N-PSKB)
- Machine learning and artificial intelligence (programme FI, N-UIZD)
- Teacher of Informatics and IT administrator (programme FI, N-UCI)
- Informatics for secondary school teachers (programme FI, N-UCI) (2)
- Computer Games Development (programme FI, N-VIZ)
- Processing and analysis of large-scale data (programme FI, N-UIZD)
- Natural language processing (programme FI, N-UIZD)
- 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
- The course is taught annually.
The course is taught: every week. - 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 2025, recent)
- Permalink: https://is.muni.cz/course/fi/spring2025/IB002