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-AG1.21 Algorithms and Graphs 1 Extent of teaching: 2P+2C Instructor: Valla T. Completion: Z,ZK Department: 18101 Credits: 5 Semester: Z Annotation:
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.
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, 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. Requirements:
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.
Chybí klíčová slova česká i anglická
Information about the course and courseware are available at https://courses.fit.cvut.cz/BIE-AG1/The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester BIE-PI.21 Computer Engineering 2021 PP 3 BIE-PV.21 Computer Systems and Virtualization 2021 PP 3 BIE-PS.21 Computer Networks and Internet 2021 PP 3 BIE-TI.21 Computer Science 2021 PP 3 BIE-SI.21 Software Engineering 2021 PP 3 BIE-IB.21 Information Security 2021 (Bachelor in English) PP 3
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