Algorithms and Data Structures 420-IS1-2ASD
Profile of studies: general academic
Form of studies: full-time
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 classes:
- - lecture : 30 h
- - exercises: 30 h
- Preparation for classes:
- - lecture: 8 h
- - exercises: 12 h
- Literature studying: 10 h
- Student's own works on computer programs, projects, reports, presentations, homeworks: 12 h
- Preparation for test: 4 h
- Preparation for exam: 8 h
- Attendance at test: 2 h
- Attendance at exam: 2 h
- Attendance at office hours: 10 h
Quantitative indicators:
- Student's workload related to activities that require direct participation of a teacher: 74 h / 3 ECTS
- Student's workload related to activities that do not require direct participation of a teacher: 54 h / 2 ECTS
Type of course
Mode
(in Polish) w sali
Course coordinators
Learning outcomes
- Knows essential notions and approaches related to designing and analysing algorithms. KA6_WG3, KA6_WG1
- Knows basic data structures and related algorithms, application examples, and implementation methods. KA6_WG3
- Knows fundamental algorithmic problems (sorting, pattern matching, and others) and selected methods for solving them. KA6_WG3
- Is able to understand the working principle of an uncomplicated algorithm and to estimate its complexity. KA6_UW6, KA6_UW4
- Is able to describe algorithms and their properties using specialist notations and terminology, drawings, examples etc. KA6_UW6, KA6_UW8
- Is able to solve uncomplicated algorithmic problems by adapting known algorithms, data structures, and approaches. KA6_UW6, KA6_UW8
- Understands the necessity for continuously improving his/her skills. KA6_UU1
Assessment criteria
Credit type: examination
Students cannot be examined before passing the exercise classes.
Bibliography
Essential bibliography:
- T.H. Cormen, C.E. Leiserson, R.L. Rivest, "Wprowadzenie do algorytmów", PWN, 2012
- R. Sedgewick, K. Wayne, "Algorytmy", Helion, 2012
- L. Banachowski, K. Diks, W. Rytter, "Algorytmy i struktury danych", PWN, 2017
Supplementary readings:
- M.T. Goodrich, R. Tamassia, M.H. Goldwasser, "Structures and Algorithms in Java/Python/C++", Wiley, 2014
- S.S. Skiena, "The Algorithm Design Manual", 2nd ed., Springer, 2008
- P. Wróblewski, "Algorytmy. Struktury danych i techniki programowania", Helion, 2015
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: