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A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.

BIE-AG2 Algorithms and Graphs 2 Extent of teaching: 2P+2C
Instructor: Completion: Z,ZK
Department: 18101 Credits: 5 Semester: L

Annotation:

Lecture syllabus:
1. Euler graphs, dominating and independent sets, colorability, distance.
2. All-pairs shortest-path algorithms.
3. Advanced network flow algorithms (inluding circulation).
4. Matching problem, Hall's matching theorem.
5. State space search, heuristics.
6. Hamilton circuit problem and the TSP problem (approximation algorithms).
7. Randomized algorithms.
8. Advanced balanced search trees - RB trees.
9. Advanced heaps (nbinomial, Fibonnaci), amortized complexity analysis.
10. B-trees.
11. Computational geometry algorithms.
12. Graphs drawing algorithms.
13. String matching agorithms.

Seminar syllabus:

Literature:
[1] Cormen, T. H. - Leiserson, C. E. - Rivest, R. L. - Stein, C.: Introduction to Algorithms, 3rd Edition, MIT Press, 2009, 978-026203384,
[2] Joyner, D. - et al.: Algorithmic Graph Theory and Sage (Version 0.8-r1991), http://code.google.com/p/graphbook/, 2014,
[3] Gross, J. L. - Yellen, J.: Graph Theory and Its Applications, 2nd Edition, Chapman and Hall, 2005, 158488505X,

Requirements:

Information about the course and courseware are available at https://courses.fit.cvut.cz/BIE-AG2/

The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester
BIE-TI.2015_ORIGINAL Computer Science (Bachelor, in English) PO 4
BIE-TI.2015 Computer Science (Bachelor, in English) PO 4
BIE-SI.21 Software Engineering 2021 V 4
BIE-PV.21 Computer Systems and Virtualization 2021 V 4
BIE-IB.21 Information Security 2021 (Bachelor in English) V 4
BIE-WSI-SI.2015 Software Engineering (Bachelor, in English) V 4
BIE-BIT.2015 Computer Security and Information technology (Bachelor, in English) V 4
BIE-PI.21 Computer Engineering 2021 V 4


Page updated 28. 3. 2024, semester: Z/2023-4, L/2019-20, L/2022-3, Z/2019-20, Z/2022-3, L/2020-1, L/2023-4, Z/2020-1, Z,L/2021-2, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška