Algorithms and Data Structures

General data

Course ID:	0600-IS1-2ASD
Erasmus code / ISCED:	(unknown) / (0613) Software and applications development and analysis 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:	(in Polish) Instytut Informatyki.
Course groups:
ECTS credit allocation (and other scores):	(not available) 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:	Guidelines and aims of teaching: To familiarize students with - the basic data structures, - techniques for solving algorithmic problems, - selected representative algorithms, - essential issues related to complexity and correctness of algorithms.
Full description:	Profile of studies: general academic Form of studies: full-time / extramural Course type: obligatory Field and discipline of science: exact and natural sciences, computer science Year of studies/semester: 2 / 3 Preliminary requirements (so-called sequential system of classes and examinations): --- Number of class hours: - lecture: 30 h - exercise classes: 30 h Didactic methods: lecture, presentation, discussion, exercise, test ECTS credits: 5 Details of student's workload (activity and number of hours): - Attendance at lecture : 15 x 2 = 30 h - Attendance at exercises: 15 x 2 = 30 h - Preparation for lectures: 15 x 1 = 15 h - Preparation for exercises: 15 x 1 = 15 h - Literature studying: 5 h - Homework: 10 h - Preparation for test: 8 h - Preparation for exam: 15 h - Attendance at exam: 2 h - Attendance at office hours: 13 h Quantitative indicators: - Student's workload related to activities that require direct participation of a teacher: 75 h / 3 ECTS - Student's workload related to practice-oriented activities: 45 / 2 ECTS
Bibliography:	Essential bibliography: - A. Levitin, "Introduction to the Design and Analysis of Algorithms", 3rd ed., Pearson, 2011 - R. Sedgewick, K. Wayne, "Algorithms", 4th ed., Helion, Addison-Wesley, 2011 - T.H. Cormen, et al., "Introduction to Algorithms", 3rd Ed., MIT Press, 2009 Supplementary readings: - S.S. Skiena, "The Algorithm Design Manual", 2nd ed., Springer, 2008 - R. Miller, L. Boxer, "Algorithms sequential and parallel: a unified approach", 2nd ed., Charles River Media, 2005
Learning outcomes:	- Knows essential notions and approaches related to designing and analysing algorithms. K_W03 - Knows basic data structures and related algorithms, application examples, and implementation methods. K_W03 - Knows fundamental algorithmic problems (sorting, pattern matching, and others) and selected methods for solving them. K_W03 - Is able to understand the working principle of an uncomplicated algorithm and to estimate its complexity. K_U06 - Is able to describe algorithms and their properties using specialist notations and terminology, drawings, examples etc. K_U06, K_U08 - Is able to solve uncomplicated algorithmic problems by adapting known algorithms, data structures, and approaches. K_U06, K_U08 - Understands the necessity for continuously improving his/her skills. K_K02 Methods for assessing learning outcomes (lecture): - written and oral test Methods for assessing learning outcomes (exercises): - written and spoken report - written and oral test - observation of student performance
Assessment methods and assessment criteria:	Form of assessment: exam

This course is not currently offered.

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