Mathematical modeling
Course: Informatics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Mathematical modeling
        
    
            Code
        
        
            ВК.4.05.01
        
    
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2022/2023
        
    
            Semester/trimester when the component is delivered
        
        
            7 Semester
        
    
            Number of ECTS credits allocated
        
        
            3
        
    
            Learning outcomes
        
        
            PLO2. Use modern mathematical apparatus of continuous and discrete analysis, linear algebra, and analytical geometry to solve theoretical and applied problems in the design and implementation of informatization objects.
PLO3. Demonstrate knowledge of the laws of random phenomena, their properties and operations on them, models of random processes, and modern software environments for solving problems of statistical processing of experimental data and construction of predictive models.
PLO4. Design, develop and analyze algorithms for solving computational and logical problems, evaluate the efficiency and complexity of algorithms based on the use of formal models of algorithms and computational functions.
PLO7. Be able to apply the methodology of simulation modeling of objects, processes, and systems, plan and conduct experiments with models, make decisions about achieving the goal based on the results of modeling.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            To successfully study the discipline "Mathematical modeling" the student must meet the following requirements:
1. Successful mastering of courses:
1) Mathematical analysis.
2) Linear algebra.
3) Differential equations.
4) Programming.
2. Knowledge of:
1) Theoretical bases and methods of construction, verification, and research of qualitative characteristics of systems.
2) Principles of building stationary and dynamic models.
3. Skills:
1) Solve systems of linear algebraic equations.
2) Solve differential equations and systems of differential equations.
3) Analyze the modeled systems.
4. Possession of:
1) Basic skills in programming and using application packages for numerical analysis (WOLFRAM MATHEMATICA, Python).
2) Skills at the application of mathematical apparatus in the construction and analysis of mathematical models.
        
    
            Course content
        
        
            The purpose of the discipline is to master theoretical and practical knowledge in the field of mathematical modeling. Mastering the methods and algorithms of construction and analysis of mathematical models of various processes.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. Matsenko, V.H. (2014). Matematychne modeliuvannia: navchalnyi posibnyk. Chernivtsi: Chernivetskyi natsionalnyi universytet.
2. Stanzhytskyi, O.M., Taran, Ye.Iu., & Hordynskyi, L.D. (2006). Osnovy matematychnoho modeliuvannia: navchalnyi posibnyk. K., VPTs “Kyivskyi universytet”.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, off-class work, the study of recommended literature.
        
    
            Assessment methods and criteria
        
        
            Semester evaluation:
The maximum score that can be received by a student: 100 points:
1. Lab work №1: - 20/12 points.
2. Lab work №2: - 20/12 points.
3. Lab work №3: - 20/12 points.
4. Lab work №4: - 20/12 points.
5. Test №1: - 20/12 points.
Final assessment (credit):
According to paragraphs. 4.6.1 and 7.1.5 "Regulations on the organization of the educational process at the Taras Shevchenko National University of Kyiv " credit is based on the current control (see semester assessment) as the sum of grades/scores on all successfully evaluated learning outcomes; scores below the minimum threshold are not included to the final score.
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Sergii
                    D.
                    Voloshchuk
                
                
                    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