This course is for PhD students, however other well motivated students are welcome, too.
In this case, please contact the dean office, if you wish to get credits for the course.
Other participants are also welcome. The lecture is open for public.
On demand of the participants, the lecture can be given in English.
Schedule:
lectures:Tuesday, 13:15-15:00, D1, room 215
tutorials: no
(the group is small, so I expect a lot of interaction in the classroom).
Basic literature:
some electronic teaching material will be available online, access with a password will be given here
Requirements:
In order to pass the course it is necessary to fulfil the following conditions:
pass the final written test
or solve some "take home exam"
The test will check understanding, skills and ability of problem solving.
It will consist of short problems (almost a test question)
that will demand certain creativity.
It is not necessary to remember details of algorithms, protocols, technical manuals, ...
but it will be necessary to understand them.
Goals:
The lecture has achieve the following educational effects:
Knowledge:
computing models
examples of advanced algorithms
computational complexity issues
Skills:
applying known algorithmic paradigms according to the relevant computing model
constructing new algorithms based on advanced paradigms
analyzing complexity of algorithms and complexity of algorithmic problems
Social competences:
ability to adjust the approach for solving a computational problem to real requirements,
ability to analyse limitations of the solution obtained,
adjusting effort to optimize the solution to economic needs.
Prerequisitives:
standard Algorithms and Data Structures knowledge,
no particular programming skills required