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
            Faculty of Computer Science and Cybernetics
                    Vasyl
                    Serhiiovych
                    Mostovyi
                
                
                    Complex systems modelling 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics
                    
                
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics