Course syllabus ALG - Algoritmizace (ŠAVŠ - WS 2018/2019)

     Czech          English          

Course title: Algoritmizace
WS 2018/2019
Course supervisor: Ing. Vladimír Beneš, Ph.D.
Supervising department:
Department of Informatics and Quantitative Methods (ŠAVŠ)
Prerequisites for registration:
Time allowance:
full-time, 2/2 (hours of lectures per week / hours of seminars per week)
part-time, 0/16 (lectures per period / seminars per period)
Type of study:
Form of teaching: lecture, seminar
Mode of completion and credits: Exam (4 credits)
Course objective:
To acquaint students with basic algorithms and data structures and their use in creating efficient algorithms. Introduce basic algorithmic constructs and algorithm design procedures. To get acquainted with basic abstract data types (field, list, tree) and frequently used data organization (search, sorting) algorithms.

The subject represents one of the basic elements of the professional part of the field of study.
Course methods:
Interpretation and lecture; Demonstration and observation, briefing; Problem solving; Front education; Individual and individualized lessons; Individual work.
By environment (in a classroom, in a classroom, self-study outside the classroom); by relationship with educated (collective, individualized).
Course content:
The content of the course has not been saved in this language version.
Learning outcomes and competences:
After completing the course, student:
Apply basic algorithms
-Apply basic and abstract data structures
Knows algorithms geared to data organization
Knows how to design algorithms

Teaching methods and workload (hours of workload):
Type of teaching method
Daily attendance
Combined form
Direct teaching
     Attendance of lectures
24 h
0 h
     Attendance of courses/seminars/tutorials
24 h
0 h
     Consultations with thesis supervisor (MT, BT)4 h0 h
     Course reading and ongoing preparation
2 h
0 h
     Ongoing evaluation
2 h
0 h
     Composing of individual (seminar) work
4 h
0 h
     Preparation for final test
4 h
0 h
     Preparation for final oral exam
10 h
0 h
     Searching, assesment and data processing (MT, BT)
4 h
0 h
     Preparation and final presentation of thesis (MT, BT)
4 h
0 h
     Writting of the thesis (BT, MT)
30 h
0 h
112 h
0 h
Assessment methods:
Requirement typeDaily attendance
Combined form
Active lecture/seminar/workshop/tutorial participation
10 %
0 %
Term paper
20 %
0 %
Mid-term test(s)
30 %
0 %
Final oral exam40 %0 %
Total100 %
0 %
Course completion:
1 "excellent" (90 - 100 %)
2 "very good" (75 - 89 %)
3 "good" (60 - 74 %)
4 "insufficient" (0 - 59 %)
Support for combined/distance forms of study:
-- item not defined --
Reading list:
Language of instruction: Czech
VIRIUS, M. Základy algoritmizace. Praha: ČVUT, 2008.

Language of instruction: Czech
MILKOVÁ, E. Algoritmy, základní konstrukce v příkladech a jejich vizualizace. Hradec Králové: Gaudeamus UHK, 2010.
Language of instruction: English
MACMILLAN, M. Data Structures and Algorithms Using C#. New York: New York: Cambridge University Press, 2007, 2007. ISBN 0-521-54765-2.

Study plans:
-- item not defined --
Run in the period of:
SS 2018/2019 (and older)
Course tutor:
Teaching language:
Czech, English
Mladá Boleslav, Praha

Last modification made by Ing. Lucie Bydžovská on 11/26/2018.

Type of output: