Algorithms and Data Structures 0600-IS1-2ASD
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
Type of course
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 criteria
Form of assessment: exam
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
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: