Information Processing Technologies

Course: Applied mathematics

Structural unit: Faculty of Computer Science and Cybernetics

Title
Information Processing Technologies
Code
ВК.2.02
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2024/2025
Semester/trimester when the component is delivered
4 Semester
Number of ECTS credits allocated
9
Learning outcomes
PLO12.2. Have knowledge of the mathematical modeling and optimal management fundamentals, to the extent necessary for the development of applied disciplines and use the relevant knowledge in the chosen profession. PLO14.2. Be able to apply professional knowledge, skills and abilities in the field of applied mathematics and computer science for research of real processes of different nature.
Form of study
Prerequisites and co-requisites
For successful study of the course “Information Processing Technologies,” the student must meet the following requirements: 1. Knowledge of: 1) Methods of construction, verification, and investigation of the qualitative characteristics of mathematical models. 2) Principles of constructing stationary, dynamic, and computer models based on well-known numerical methods. 2. Ability to: 1) Conduct studies of the qualitative characteristics of constructed mathematical models. 2) Formulate mathematical optimization problems for such models. 3) Apply methods of mathematical and computer modeling to the study of information processes. 3. Proficiency in: 1) Basic skills in using application software packages for numerical analysis (MATLAB). 2) English at a level not lower than Intermediate.
Course content
The aim of the course is for students to master constructive approaches to numerical methods of information processing in various applied contexts. Students will be introduced to methods of information analysis, its optimal compression, storage or recovery, as well as the development of software products for this purpose.
Recommended or required reading and other learning resources/tools
1. I. Parkhomei, N. Tsopa. Osnovy teorii informatsiinykh protsesiv, Chastyna 2. Systemy obrobky syhnaliv, Kyiv, KPI im. Ihoria Sikorskoho, 2020. 2. V.L. Kozhevnykov, A.V. Kozhevnykov. Teoriia informatsii ta koduvannia. Dnipropetrovsk, NHU, 2012. 3. Hansen J.S. GNU Octave Beginner’s Guide, Packt Publishing, 2011. 4. A.I. Nakonechnyi, R.A. Nakonechnyi, V.A. Pavlysh. Tsyfrova obrobka syhnaliv, Lviv, 2010.
Planned learning activities and teaching methods
Lectures, seminars, independent work.
Assessment methods and criteria
Semester Assessment: The maximum number of points a student can earn is 100. 1. Test №1: 30/18 points. 2. Test №2: 30/18 points. 3. Ongoing assessment: 40/24 points. Final grade in the form of a pass/fail credit: Credit points are determined as the sum of the scores for all successfully assessed learning outcomes provided by this program. The minimum threshold for the total score across all components is 60% of the possible number of points. A student receives a positive overall grade in the discipline if their semester score is at least 60 points.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Irada Dzhalladova
Complex systems modelling
Faculty of Computer Science and Cybernetics
Vasyl Serhiiovych Mostovyi
Complex systems modelling
Faculty of Computer Science and Cybernetics