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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

Algorithms and Graphs 1

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Code Completion Credits Range Language
BIE-AG1 Z,ZK 6 2P+2C English
Lecturer:
Pavel Tvrdík (guarantor), Jiřina Scholtzová
Tutor:
Pavel Tvrdík (guarantor), Jiřina Scholtzová
Supervisor:
Department of Theoretical Computer Science
Synopsis:

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.

Requirements:

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.

Syllabus of lectures:

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.

Syllabus of tutorials:

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.

Study Objective:
Study materials:

[1] Cormen, T. H. - Leiserson, C. E. - Rivest, R. L. - Stein, C.: Introduction to Algorithms, 3rd Edition, MIT Press, 2009, 978-0262033848,

[2] Gibbons, A.: Algorithmic Graph Theory, Cambridge University Press, 1985, 978-0521288811,

[3] Gross, J. L. - Yellen, J. - Zhang, P.: Handbook of Graph Theory, 2nd Edition (Discrete Mathematics and Its Applications), Chapman and Hall/CRC, 2013, 978-1439880180,

Note:
Further information:
https://courses.fit.cvut.cz/BIE-AG1/
Time-table for winter semester 2019/2020:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue
roomTH:A-1247
Scholtzová J.
11:00–12:30
(lecture parallel1)
Thákurova 7 (FSv-budova A)
seminární místnost
roomTH:A-1247
Scholtzová J.
12:45–14:15
(lecture parallel1
parallel nr.101)

Thákurova 7 (FSv-budova A)
seminární místnost
Fri
Thu
Fri
Time-table for summer semester 2019/2020:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2020-08-06
For updated information see http://bilakniha.cvut.cz/en/predmet3464306.html