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.
BI-AVI.21 Algorithms visually Extent of teaching: 2P+1C Instructor: Kučera L. Completion: Z,ZK Department: 18101 Credits: 4 Semester: L Annotation:
The course complements other algorithm courses at FIT. It brings knowledge about particular important algorithms from different fields of the computer science that extend substantially knowledge presented in BI-AG1 and BI-AG2. A wide scope of covered subject is made possible due to using visualization bz Algovision (www.algovision.org<http://www.algovision.org>) that make understanding the principles of algorithms easy.
Lecture syllabus:
1. Tree data structures (general methods and algorithms that are not included in AG1 and AG2, e.g., red-black trees) 2. Shortest paths (algorithm invariant view of Dijkstra and Bellman-Ford algorithms) 3. Efficient network flow algorithms - augmenting path methods (Dinitz and 3 Indiens) 4. Efficient network flow algorithms - preflow methods (Goldberg) 5. Discrete Fourier transform, cosine transform and the FFT algorithm 6. Binary number addition algorithms (Kogge-Stone, Ladner-Fischer, Brent-Kung) 7. Geometric algorithms (convex hull, Voronoi diagram - Fortune) 8. Sorting and switching networks (bitonic sort, odd-even sort) 9. Conjugated gradients method 10. Eigenvector and eigenvalue applications (graph min-cut spectral algorithm) 11. Linear programming (simplex method and duality) 12. Quantum algorithms (basic notions - qubit, entanglement) 13. Quantum algorithms (Algorithms of Groover and Simon with a light outline of Shor factorization) Seminar syllabus:
1. Tree data structures (general methods and algorithms that are not included in AG1 and AG2, e.g., red-black trees) 2. Shortest paths (algorithm invariant view of Dijkstra and Bellman-Ford algorithms) 3. Efficient network flow algorithms - augmenting path methods (Dinitz and 3 Indiens) 4. Efficient network flow algorithms - preflow methods (Goldberg) 5. Discrete Fourier transform, cosine transform and the FFT algorithm 6. Binary number addition algorithms (Kogge-Stone, Ladner-Fischer, Brent-Kung) 7. Geometric algorithms (convex hull, Voronoi diagram - Fortune) 8. Sorting and switching networks (bitonic sort, odd-even sort) 9. Conjugated gradients method 10. Eigenvector and eigenvalue applications (graph min-cut spectral algorithm) 11. Linear programming (simplex method and duality) 12. Quantum algorithms (basic notions - qubit, entanglement) 13. Quantum algorithms (Algorithms of Groover and Simon with a light outline of Shor factorization) Literature:
1. L. Kučera: Algovize, aneb procházka krajinou algoritmů, Blatenská tiskárna, 2009, ISBN 8090293859, 9788090293854. Dostupné z http://www.algovision.org 2. T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein: Introduction to Algorithms, MIT Press, 1990, 2009, ISBN 978-0-262-03384-8 3. B. Barak, S. Arora: Computational Complexity: A Modern Approach, 2007, Cambridge Univ. Press, ISBN 978-0521424264 Requirements:
There are no input knowledge requirements.
Chybí požadavky. The course is also part of the following Study plans:
Page updated 20. 4. 2024, semester: L/2023-4, L/2020-1, L/2022-3, L/2021-2, Z/2019-20, Z/2022-3, Z/2020-1, Z/2023-4, L/2019-20, Z/2021-2, Z/2024-5, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška