Faculty of Engineering and Natural Sciences
Department of Electrical and Electronic Engineering

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

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.

  1. Introduction
  2. Linear Equations and Matrices
  3. Linear Equations and Matrices
  4. Solving Linear Systems
  5. Determinants
  6. Real Vector Spaces
  7. Real Vector Spaces
  8. Midterm
  9. Linear Transformation and Matrices
  10. Linear Transformation and Matrices
  11. Eigen Values and Eigenvectors
  12. Eigen Values and Eigenvectors
  13. MATLAB for Linear Algebra
  14. MATLAB Applications in Linear Algebra and MATLAB Exercises
  15. Revision

  1. Tutorials
  2. Tutorils
  3. Tutorils
  4. Quiz
  5. Tutorils
  6. quiz
  7. Tutorils

  1. Tutorils
  2. Tutorils
  3. quiz
  4. Tutorils
  5. quiz
  6. Tutorils
  7. Tutorils
  8. Revision

  • Interactive Lectures
  • Practical Sessions
  • Excersises
  • Presentation
  • Assignments
  • Case Studies
Description (%)
Method Quantity Percentage (%)
Midterm Exam(s)25
Final Exam145
Total: 100
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)
  • 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
Activities Quantity Duration (Hour) Total Work Load
Lecture (14 weeks x Lecture hours per week)20
Laboratory / Practice (14 weeks x Laboratory/Practice hours per week) 20
Midterm Examination (1 week) 20
Final Examination(1 week) 20
Preparation for Midterm Examination 0
Preparation for Final Examination4 0
Assignment / Homework/ Project 0
Seminar / Presentation 0
Total Workload: 0
ECTS Credit (Total workload/25): 0