Algorithms and Graphs 1
| Kód | Zakončení | Kredity | Rozsah | Jazyk výuky |
|---|---|---|---|---|
| BIE-AG1.21 | Z,ZK | 5 | 2P+2C | anglicky |
- Garant předmětu:
- Dušan Knop
- Přednášející:
- Tomáš Valla
- Cvičící:
- Dušan Knop, Maria Saumell Mendiola, Jiřina Scholtzová
- Předmět zajišťuje:
- katedra teoretické informatiky
- Anotace:
-
The course covers the basics from the efficient algorithm design, data structures, and graph theory, belonging to the core knowledge of every computing curriculum. It is interlinked with the concurrent BIE-AAG and BIE-ZDM courses in which the students gain the basic skills and knowledge needed for time and space complexity of algorithms and learn to handle practically the asymptotic mathematics.
- Požadavky:
-
Entry knowledge: Active algorithmic skills for solving basic types of computational tasks, programming skills in some HLL (Java, C++), and knowledge of basic notions from the mathematical analysis and combinatorics are expected. Students are expected to take concurrent courses BIE-AAG and BIE-ZDM.
- Osnova přednášek:
-
1. Motivation and Elements of Graph Theory.
2. Basic Definitions and Elements of Graph Theory I.
3. Basic Definitions and Elements of Graph Theory II.
4. Sorting Algorithms O(n^2). Binary Heaps and HeapSort.
5. Extendable Array, Amortized Complexity, Binomial Heaps.
6. Search Trees and Balance Strategies.
7. Introduction to Randomization, Hashing.
8. Recursive algorithm and the Divide-and-Conquer method.
9. Probabilistic Algorithms and Their Complexity. QuickSort.
10. Dynamic Programming.
11. Minimum Spanning Trees.
12. Shortest Paths Algorithms on Graphs.
- Osnova cvičení:
-
1. Motivation and Elements of Graph Theory I.
2. Elements of Graph Theory II.
3. Elements of Graph Theory III. 1st ProgTest.
4. Sorting Algorithms O(n^2). Binary Heaps.
5. Extendable Array, Amortized Complexity, Binomial Heaps.
6. Search Trees and Balance Strategies. 2nd ProgTest.
7. Hashing and Hash tables.
8. Recursive Algorithms and Divide et Impera Method.
9. Probabilistic Algorithms and their Complexity. QuickSort.
10. Semestral test.
11. Dynamic Programming. 3rd ProgTest.
13. Minimum Spanning Trees, Shortest Paths.
- Cíle studia:
- Studijní materiály:
-
1. Cormen T.H., Leiserson C.E., Rivest R.L., Stein C. : Introduction to Algorithms (3rd Edition). MIT Press, 2016. ISBN 978-0262033848.
2. Wengrow J. : A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills (2nd Edition). Pragmatic Bookshelf, 2020. ISBN 978-1680507225.
3. Sedgewick R. : Algorithms (4th Edition). Addison-Wesley, 2011. ISBN 978-0321573513.
4. Deo N. : Graph Theory with Applications to Engineering and Computer Science. Dover Publications, 2016. ISBN 978-048680793.
5. Bickle A. : Fundamentals of Graph Theory. AMS, 2020. ISBN 978-1470453428.
- Poznámka:
-
Chybí klíčová slova česká i anglická
Information about the course and courseware are available at https://courses.fit.cvut.cz/BIE-AG1/
- Další informace:
- https://courses.fit.cvut.cz/BIE-AG1/
- Rozvrh na zimní semestr 2024/2025:
- Rozvrh není připraven
- Rozvrh na letní semestr 2024/2025:
- Rozvrh není připraven
- Předmět je součástí následujících studijních plánů:
-
- Bachelor specialization, Computer Engineering, 2021 (povinný předmět programu)
- Bachelor specialization, Information Security, 2021 (povinný předmět programu)
- Bachelor specialization, Software Engineering, 2021 (povinný předmět programu)
- Bachelor specialization, Computer Science, 2021 (povinný předmět programu)
- Bachelor specialization, Computer Networks and Internet, 2021 (povinný předmět programu)
- Bachelor specialization Computer Systems and Virtualization, 2021 (povinný předmět programu)