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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.

BI-AG1 Algorithms and Graphs 1 Extent of teaching: 2P+2C
Instructor: Completion: Z,ZK
Department: 18101 Credits: 6 Semester: Z

Annotation:
The course covers the basics of efficient algorithm design, data structures, and graph theory, belonging to the core knowledge of every computing curriculum. It links and partially develops the knowledge from the course BI-DML.21, in which students acquire the knowledge and skills in combinatorics necessary for evaluating the time and space complexity of algorithms. The course also follows up knowledge from BI-MA1.21, the practical usage of asymptotic mathematics, in particular, the asymptotic notation.

Lecture syllabus:
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.

Seminar syllabus:
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.

Literature:
[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,

Requirements:
Active algorithmic skills for solving basic types of computational tasks, C++ programming skills, and knowledge of basic notions from mathematical analysis and combinatorics are expected. Students should take the concurrent course BIE-AAG.21.

Informace o předmětu a výukové materiály naleznete na https://courses.fit.cvut.cz/BI-AG1/
Na tento předmět navazuje v magisterském studiu předmět Paralelní a distribuované programování.

The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester
BI-SPOL.2015 Unspecified Branch/Specialisation of Study PP 3
BI-WSI-PG.2015 Web and Software Engineering PP 3
BI-WSI-WI.2015 Web and Software Engineering PP 3
BI-WSI-SI.2015 Web and Software Engineering PP 3
BI-ISM.2015 Information Systems and Management PP 3
BI-ZI.2018 Knowledge Engineering PP 3
BI-PI.2015 Computer engineering PP 3
BI-TI.2015 Computer Science PP 3
BI-BIT.2015 Computer Security and Information technology PP 3


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