(in Polish) Algorithms and Data Structures 510-IS1-2ASD-23-ENG
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, offfice hours.
ECTS credits: 4
Details of student's workload (activity and number of hours):
- Attendance at classes:
- - lecture : 30 h
- - exercises: 30 h
- Preparation for classes:
- - exercises: 10 h
- Literature studying: 5 h
- Student's own works on computer programs, projects, reports, presentations, homeworks: 10 h
- Preparation for exam: 8 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: 67 h / 2.7 ECTS
- Student's workload related to activities that do not require direct participation of a teacher: 33 h / 1.3 ECTS
Type of course
Mode
(in Polish) w sali
Course coordinators
Learning outcomes
- Knows essential notions and approaches related to designing and analysing algorithms. KP6_WG3, KP6_WG1
- Knows basic data structures and related algorithms, application examples, and implementation methods. KP6_WG3
- Knows fundamental algorithmic problems (sorting, pattern matching, and others) and selected methods for solving them. KP6_WG3
- Is able to understand the working principle of an uncomplicated algorithm and to estimate its complexity. KP6_UW6, KP6_UW4
- Is able to describe algorithms and their properties using specialist notations and terminology, drawings, examples etc. KP6_UW6, KP6_UW8
- Is able to solve uncomplicated algorithmic problems by adapting known algorithms, data structures, and approaches. KP6_UW6, KP6_UW8
- Understands the necessity for continuously improving his/her skills. KP6_UU1
Assessment criteria
Credit type: examination
Students cannot be examined before passing the exercise classes.
Rules of AI usage v.25.09.29
Students can use AI systems only to the extent permitted by law acts adopted by the University and Faculty, to automatize mechanic actions that require nether creative nor critical thinking, and that do not require understanding processes and technologies.
Students are prohibited from using AI to do tasks that aim to develop students' creativity, skills and knowledge, that should be solved without automatization in order to ensure the learning outcomes.
Questions and doubts about AI usage should be communicated to the teacher.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: