INTERNATIONAL BURCH UNIVERSITY
Faculty of Engineering and Natural Sciences
Department of Information Technologies
20162017
SYLLABUS 
Code 
Name 
Level 
Year 
Semester 
MTH 204 
Numerical Analysis 
Undergraduate 
2 
Spring 
Status 
Number of ECTS Credits 
Class Hours Per Week 
Total Hours Per Semester 
Language 
Compulsory 
5 
2 + 2 
100 

Instructor 
Assistant 
Coordinator 
Mehrija Hasičić, Senior Teaching Assistant 
Assoc. Prof. Dr. Željko Jurić 
Željko Jurić, Assoc. Prof. Dr. 
[email protected] 
[email protected] 
no email 
Numerical methods for various types of linear systems of equations (full, triangular, banded), the least squares method for
inconsistent systems, nonlinear equations (scalar and system), eigenvalue problem, integration, derivation, interpolation and
initial and boundary value problems for ODE. Basic technologies for numerical methods, as iteration, linearisation,
discretisation and extrapolation, and theoretical concepts as order of accuracy, speed of convergence, complexity, condition and
stability. Numerical solution to PDE problems by means of mathematical software 
COURSE OBJECTIVE 
The purpose of numerical analysis is twofold:
(1) to find acceptable approximate solutions when exact solutions are either impossible or so arduous and timeconsuming as to
be impractical, and
(2) to devise alternate methods of solution better suited to the capabilities of computers. 
COURSE CONTENT 
 Introduction to MATLAB and MATLAB Usage
 MATLAB Fundamentals and MATLAB Symbolic Toolbox
 Vectors and Matrices
 Data Input/Output, Program Flow Control
 Function Creation and Selected MATLAB Functions
 2D Graphics
 3D Graphics
 Midterm
 GUI and MATLAB Applications
 Introduction to Numerical Methods: Equations, Integration, Numerical Differentiation, Firstorder differential Equations, Linear Ordinary Differential Equations, RungeKutta Methods, Partial Differential Equations
 Linear Equations and Interpolation
 Zeros, Roots, Least Squares
 Quadrature, Integration, Differential Equations
 Eigenvalues, Singular Values, Random Number Generation
 Numerical Analysis Application

LABORATORY/PRACTICE PLAN 
 Introduction to MATLAB and MATLAB Usage
 MATLAB Fundamentals and MATLAB Symbolic Toolbox
 Vectors and Matrices
 Data Input/Output, Program Flow Control
 Function Creation and Selected MATLAB Functions

 2D Graphics
 3D Graphics
 Midterm
 GUI and MATLAB Applications
 Introduction to Numerical Methods: Equations, Integration, Numerical Differentiation, Firstorder differential Equations, Linear Ordinary Differential Equations, RungeKutta Methods, Partial Differential Equations
 Linear Equations and Interpolation
 Zeros, Roots, Least Squares
 Quadrature, Integration, Differential Equations
 Eigenvalues, Singular Values, Random Number Generation
 Numerical Analysis Application

Description 
 Interactive Lectures
 Practical Sessions
 Excersises
 Presentation
 Assignments

Learning outcomes 
 identify different mathematical problems and reformulate them in a way that is appropriate for numerical treatment
 choose appropriate numerical method for treatment of the given problem
 explain choice of method by accounting for advantages and limitations
 choose an algorithm that implies efficient calculations and implement it in a programming language, suited for calculations, e.g. Matlab
 present the results in a relevant and illustrative way
 estimate the reliability of the results
 use functions from the programming language library for efficient calculations and visualisation

TEXTBOOK(S) 
 T. Siauw & A. M. Bayen \\\\\\\\\\\\\\\"An Introductionto MATLAB® Programming and Numerical Methods for Engineers\\\\\\\\\\\\\\\"

ECTS (Allocated based on student) WORKLOAD 
Lecture (14 weeks x Lecture hours per week)  14  2  28  Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)  14  2  28  Midterm Examination (1 week)  1  2  2  Final Examination(1 week)  1  2  2  Preparation for Midterm Examination  1  10  10  Preparation for Final Examination  1  10  10  Assignment / Homework/ Project  2  10  20  Seminar / Presentation    0 

