INTERNATIONAL BURCH UNIVERSITY
Faculty of Engineering and Natural Sciences
Department of Electrical and Electronic Engineering
20162017
SYLLABUS 
Code 
Name 
Level 
Year 
Semester 
MTH 103 
Linear Algebra 
Undergraduate 
1 
Fall 
Status 
Number of ECTS Credits 
Class Hours Per Week 
Total Hours Per Semester 
Language 
Compulsory 
5 
2 + 2 
0 
English 
Instructor 
Assistant 
Coordinator 
Jasna Hivziefendić, Assoc. Prof. Dr. 
Jasna Hivziefendic 
Jasna Hivziefendić, Assoc. Prof. Dr. 
[email protected] 
[email protected] 
no email 
Linear algebra is the study of linear systems of equations, vector spaces, and linear transformations. Solving systems of linear equations is a basic tool of many mathematical procedures used for solving problems in science and engineering. Sufficient knowledge in this field can assist students in learning other (more applicable) courses as Linear Programming Problems, Operations Research, Problems of Optimization ,etc. Topics include: systems of linear equations, the basic arithmetic operations on vectors and matrices, determinants and inverses, linear combinations and linear independence, abstract vector spaces, inner product spaces, orthogonal bases and orthogonal projections, eigenvalues and eigenvectors. Some applications of linear algebra will be discussed, such as computer graphics, Kirchoff’s laws, linear regression (least squares), differential equations 
COURSE OBJECTIVE 
Students will be able to apply the concepts and methods described in the syllabus, they will be able to solve problems using linear algebra, they will know a number of applications of linear algebra, and they will be able to follow complex logical arguments and develop modest logical arguments. The text and class discussion will introduce the concepts, methods, applications, and logical arguments; students will practice them and solve problems on daily assignments, and they will be tested on quizzes, midterms, and the final. 
COURSE CONTENT 
 Introduction
 Linear Equations and Matrices
 Linear Equations and Matrices
 Solving Linear Systems
 Determinants
 Real Vector Spaces
 Real Vector Spaces
 Midterm
 Linear Transformation and Matrices
 Linear Transformation and Matrices
 Eigen Values and Eigenvectors
 Eigen Values and Eigenvectors
 MATLAB for Linear Algebra
 MATLAB Applications in Linear Algebra and MATLAB Exercises
 Revision

LABORATORY/PRACTICE PLAN 
 Tutorials
 Tutorils
 Tutorils
 Quiz
 Tutorils
 quiz
 Tutorils

 Tutorils
 Tutorils
 quiz
 Tutorils
 quiz
 Tutorils
 Tutorils
 Revision

Description 
 Interactive Lectures
 Practical Sessions
 Excersises
 Presentation
 Assignments
 Case Studies

Description (%) 
Quiz   20  Homework   10  Midterm Exam(s)   25  Laboratory    Final Exam  1  45 

Learning outcomes 
 Formulate, solve, apply, and interpret systems of linear equations in several variables;
 2. Solve systems of linear equations using multiple methods, including Gaussian elimination and matrix inversion
 Carry out matrix operations, including inverses and determinants
 Demonstrate elementary facts in abstract vector spaces
 Demonstrate understanding of linear independence, span, and basis
 Decompose linear transformations according to their spectra (eigenvectors and eigenvalues)

TEXTBOOK(S) 
 Bernard Kolman, David R. Hill, “Elementary Linear Algebra with Applications”, Pearson Hall, 9th edition, 2008.
 Introduction to Linear Algebra, 4th Edition by Gilbert Strang

ECTS (Allocated based on student) WORKLOAD 
Lecture (14 weeks x Lecture hours per week)   2  0  Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)   2  0  Midterm Examination (1 week)   2  0  Final Examination(1 week)   2  0  Preparation for Midterm Examination    0  Preparation for Final Examination  4   0  Assignment / Homework/ Project    0  Seminar / Presentation    0 

