Algorithms and data structures II 400-IS1-2AS2
Profile of studies: practical
Form of studies: full-time
Course type: obligatory
Field and discipline of science: exact and natural sciences, computer science
Year of studies/semester: 2 / 4
Prerequisites:
- Algorithms and data structures I
Number of class hours:
- lecture: 15 h
- laboratory classes: 15 h
- project laboratory classes: 15 h
Didactic methods: lecture, presentation, discussion, laboratory, project.
ECTS credits: 4
Details of student's workload (activity and number of hours):
- Attendance at classes:
- - lecture : 15 h
- - laboratory: 15 h
- - project laboratory: 15 h
- Preparation for classes: 5h
- Literature studying: 20 h
- Student's own works on computer programs, projects, reports, presentations, homeworks: 12 h
- Preparation for exam: 11 h
- Attendance at exam: 2 h
- Attendance at office hours: 5 h
Quantitative indicators:
- Student's workload related to activities that require direct participation of a teacher: 52 h / 2,1 ECTS
- Student's workload related to activities that do not require direct participation of a teacher: 42 h / 1,7 ECTS
Type of course
Mode
(in Polish) w sali
Requirements
Prerequisites (description)
Course coordinators
Learning outcomes
- Has got enhanced knowledge of algorithms, data structures, and methods for implementing them. KP7_WG1
- Knows techniques for solving difficult algorithmic problems. KP7_WG1
- Is able to develop a solution to a nontrivial algorithmic problem and to study the solution with respect to correctness and complexity. KP7_UO4, KP7_UK4, KP7_UW3
- Is able to implement a complicated algorithm as a computer program, optimizing computations and memory usage. KP7_UO4, KP7_UK4, KP7_UW3
- Is able to retrieve, evaluate, and integrate informations related to a problem, so as to develop an optimal algorithmic solution. KP7_UU1
- Understands the necessity for continuously improving his/her skills. KP7_UU2
Assessment criteria
Credit type: examination
Students cannot be examined before passing the laboratory classes.
Bibliography
Essential bibliography:
- T.H. Cormen, C.E. Leiserson, R.L. Rivest, "Wprowadzenie do algorytmów", PWN, 2012
- R. Sedgewick, K. Wayne, "Algorytmy", Wyd. 4, 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
- P. Wróblewski, "Algorytmy. Struktury danych i techniki programowania", Wyd. 5, Helion, 2015
- A. Drozdek, "C++. Algorytmy i struktury danych", Helion, 2004
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: