Programming
Course: System Analysis
Structural unit: Faculty of Computer Science and Cybernetics
Title
Programming
Code
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2022/2023
Semester/trimester when the component is delivered
1 Semester
Number of ECTS credits allocated
8
Learning outcomes
Know the basic concepts of programming and principles of program development.
Know the basic classical algorithms and types of data structures.
Be able to design, develop and test programs.
Justify your own view of the problem, communicate with colleagues on the design and development of programs, compile reports.
Organize your independent work to achieve results.
Be responsible for the work performed, be responsible for their quality.
Form of study
Full-time form
Prerequisites and co-requisites
1. Know mathematics and computer science in the scope of school courses.
2. Be able to apply knowledge of natural sciences school course to problem solving.
3. Have basic computer skills.
Course content
The discipline deals with such sections as numerical and other data representation, organization of computational order management, exceptions, routines, recursion, iteration, data organization, containers, iteration, numerical data processing, file processing, classes and encapsulation, inheritance, event-driven programming, data structures, graph processing.
It is taught in the 1st and 2nd semesters of the 1st year in the amount of 280 hours. (8 ECTS credits) in particular: lectures - 56 hours, laboratory - 58 hours, consultations - 4 hours, independent work - 122 hours. The course includes 4 tests (2 each semester). The first semester of study ends with a test, the second semester of study - an exam.
Recommended or required reading and other learning resources/tools
1. Python 3.9 documentation.– https://docs.python.org/3/
2. We study Python. / M. Lutz. - Dialectics, 2019.
3. Informatics and programming. Python-based course. Lecture materials: textbook. way. / OV Obvintsev; Kyiv. nat. Univ. Taras Shevchenko. - Kyiv: Osnova, 2017. - 247 p.
4. Object-oriented programming. Python-based course: lecture materials: textbook. way. / Obvintsev OV; Kyiv. nat. Univ. Taras Shevchenko. - Kyiv: Osnova, 2017. - 324 p.
5. Cormen T. Algorithms. Construction and analysis. / Cormen T., Leiserson C., Rivest R., Stein K. - M .: Williams, 2005. - 1296 p.
Planned learning activities and teaching methods
Lecture, laboratory work, independent work
Assessment methods and criteria
Test work, defense of laboratory work, exam, test
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline