Course: Algorithms and data structure 1

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Course title Algorithms and data structure 1
Course code KMI/ADS1
Organizational form of instruction Lecture
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 3
Language of instruction Czech
Status of course Optional
Form of instruction Face-to-face
Work placements unspecified
Recommended optional programme components None
  • Beránek Ladislav, doc. Ing. CSc.
  • Remeš Radim, Mgr.
Course content
Lectures: 1. Basic algorithmic construction; 2. Method of algorithm design; 3. Basic principles of algorithms evaluation; 4. Algorithmic construction; a. work with sequence; b. work with matrixes; 5. Data structures; a. compact and linked lists; b. stack, queue, heap; 6. Sorting algorithms; a. direct method; b. quicksort, heapsort; 7. Trees, hash tables - basic principles;

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Demonstration, E-learning
  • Preparation for classes - 12 hours per semester
  • Preparation for credit - 20 hours per semester
  • Semestral paper - 20 hours per semester
  • Class attendance - 32 hours per semester
Learning outcomes
The students become acquainted in this course with the basic data structures and their usage at effective algorithm design. Students will master the basic algorithmic constructions and procedures for algorithm development. The overview of basic abstract data type (field, list, tree, dictionary) and often used algorithms aimed above all on data organization (sorting, searching) is in practice the main part of this course.
Students will understand the basic principles of algorithms, they will be able to create simpler algorithms and use them at their own programs design
The course has no prerequisities.

Assessment methods and criteria
Student performance assessment, Test

Credit Requirements: Processing of partial tasks. Preparation of the semester project.
Recommended literature
  • CORMEN, T. H., LEISERSON, CH. E. RIVEST, R. R. Introduction to Algorithms.. Cambridge : MIT Press, 2002. ISBN 0-262-03293-7.
  • Edmonds, J. How to Think about Algorithms.. Cambridge: University Press, 2008.
  • Jamro, M. C# Data Structures and Algorithms. Birmingham, UK: Packt, 2018. ISBN 978-1-78883-373-8.
  • MCMILLAN, M. Data Structures and Algorithms Using C#. New York: Cambridge University Press, 2007.. Cambridge: University Press, 2007. ISBN 0-521-54765-2.
  • Preiss, B. R. Data Structures and Algorithms whit Object-Oriented Design Patterns in Java. New York: John Wiley & Sons, 2000. ISBN 0-471-34613-6.
  • Prokop, J. Algoritmy v jazyku C a C++. Praha: Computer Press, 2015. ISBN 978-80-247-5467-3.
  • Sedgewick, R. Algorithms in Java.. New York: Addison Wesley, 1999.
  • Sedgewick, R. Algoritmy v C#.. New York: Softpress, 2003.
  • Wirth, N. Algoritmy a štruktúry údajov.. Bratislava: Alfa, 1989.
  • Wróblewski, P. Algoritmy. Praha: Computer Press, 2015. ISBN 9788025141267.

Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Economics Study plan (Version): Economic Informatics (4) Category: Economy - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Economics Study plan (Version): Financial and Insurance Mathematics (4) Category: Mathematics courses - Recommended year of study:-, Recommended semester: Summer