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Lecturer(s)
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Course content
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1. Basic concepts of computers and programming; programs and programming languages; conventions and comments; data types; variables, declarations, assignments, operators 2. Terminal input and output; command line 3. Basic mathematical functions; random numbers; program validation, debugging 4. Control structures (branching and cycles) 5. Subroutines, return value, parameters; magic numbers and constants 6. Classes and objects; memory layout 7. Arrays, multidimensional arrays, arrays of objects; 8. Examples of fields, methods, and objects 9. Strings; work with characters; algorithm design procedure 10. Basic sorting and searching algorithms 11. Exceptions; working with files and folders; file input and output 12. Display of data in computer memory, coding of integers and real numbers, characters; comparison of object-oriented and procedural programming
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Learning activities and teaching methods
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- Contact hours
- 26 hours per semester
- Preparation for comprehensive test (10-40)
- 26 hours per semester
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| prerequisite |
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| Knowledge |
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| Describe the fundamental principles of how a computer and its operating system work. Explain the basics of propositional logic Explain how to solve systems of linear equations. |
| Skills |
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| use the operating system (install and run applications) |
| work with the file system (create, copy and delete files and folders) |
| Competences |
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| N/A |
| N/A |
| N/A |
| N/A |
| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| characterize the basic language constructions and data structures of the programming language |
| explain the basic approaches for algorithm design |
| characterize ways of creating, verifying and debugging programs |
| explain basic sorting and searching algorithms |
| characterize work with files |
| compile and implement programs in python |
| Skills |
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| analyze and solve simple problems |
| design and implement programs in the selected programming language |
| apply basic sorting and searching algorithms |
| Competences |
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| N/A |
| teaching methods |
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| Knowledge |
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| Practicum |
| Task-based study method |
| Skills |
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| Practicum |
| Competences |
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| Practicum |
| Task-based study method |
| assessment methods |
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| Knowledge |
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| Test |
| Professional knowledge is assessed through the completion of tasks during in-person classes. |
| Skills |
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| Test |
| Professional skills are verified by completing and submitting assignments during in-person classes. |
| Competences |
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| Test |
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Recommended literature
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Beazley, David M. Python : referenční programátorská příručka. Praha : Neocortex, 2002. ISBN 80-86330-05-2.
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Lutz, Mark; Ascher, David. Naučte se Python. 1. vyd. Praha : Grada Publishing, 2003. ISBN 80-247-0367-X.
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Wróblewski, Piotr. Algoritmy : datové struktury a programovací techniky. Vyd. 1. Brno : Computer Press, 2004. ISBN 80-251-0343-9.
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