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Algorithms and data structures

General data

Course ID:	1000-712ASD
Erasmus code / ISCED:	11.302 The subject classification code consists of three to five digits, where the first three represent the classification of the discipline according to the Discipline code list applicable to the Socrates/Erasmus program, the fourth (usually 0) - possible further specification of discipline information, the fifth - the degree of subject determined based on the year of study for which the subject is intended. / (0612) Database and network design and administration The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Algorithms and data structures
Name in Polish:	Algorytmy i struktury danych
Organizational unit:	Faculty of Mathematics, Informatics, and Mechanics
Course groups:	Obligatory courses for 2nd year Bioinformatics
ECTS credit allocation (and other scores):	4.50 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Type of course:	obligatory courses
Short description:	Algorithm design and analysis. Survey of fundamental algorithms and data structures. Improving practical programming and algorithm development skills. Applying ready to use libraries of algorithms and data structures.
Full description:	Basic methods of design and analysis of algorithms and data structures. Programming (algorithm coding, library usage). Text algorithms (pattern matching) and text data structures (suffix trees and tables). Graph algorithms (computer graph representation, searching, path problems, tree algorithms). Algorithms and data structures in computational biology (sequence alignment, phylogenetic trees).
Bibliography:	Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford (2001). Introduction to Algorithms (2nd ed.). MIT Press and McGraw-Hill. ISBN 0-262-53196-8.
Learning outcomes:	Knowledge: - knows the basic methods of designing, analyzing and programming algorithms, including search algorithms, graph algorithms, path problems - knows the basic data structures and operations performed on them, with particular emphasis on data structures used in computational biology Skills: -designs, analyzes in terms of correctness and computational complexity, and programs algorithms; uses basic algorithmic techniques and data structures - uses the accepted formats of representation of various types of data according to the situation (numbers, tables, text) bearing in mind their limitations
Assessment methods and assessment criteria:	test + project + writing exam

Classes in period "Summer semester 2025/26" (past)

Time span:	2026-02-16 - 2026-06-07	Selected timetable range: weekly course term Go to timetable MO WYK LAB CW TU W TH LAB CW FR
Type of class:	Classes, 15 hours more information Lab, 15 hours more information Lecture, 30 hours more information
Coordinators:	Norbert Dojer
Group instructors:	Adam Cicherski, Norbert Dojer, Damian Wójtowicz
Students list:	(inaccessible to you)
Credit:	Course - Examination Lecture - Examination

Classes in period "Summer semester 2026/27" (future)

Time span:	2027-02-15 - 2027-06-06	Selected timetable range: weekly course term Go to timetable
Type of class:	Lab, 30 hours more information Lecture, 30 hours more information
Coordinators:	Norbert Dojer
Group instructors:	Adam Cicherski, Jadwiga Czyżewska, Norbert Dojer, Kacper Kluk, Damian Wójtowicz
Students list:	(inaccessible to you)
Credit:	Course - Examination Lecture - Examination

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