Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
3MATH211Linear Algebra3+0+03603.11.2026
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program Electrical - Electronic Engineering
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course The course is standard first year course on linear algebra providing basic definitions, concepts and methods. Discussion and proofs are given in form of algorithms whenever is possible. The objective Concepts of basic operations in Linear algebra: Introduction to Systems of Linear Equations, Gaussian Elimination, Matrices and Matrix Operations. Inverses; Rules of Matrix Arithmetic, Elementary is twofold: to make students ready to see applications of linear algebra on subsequent courses and to enable them to continue their study on more advanced level.
Course Content Systems of linear equations. Matrices. Algebraic properties of matrix operations. Special types of matrices. Echelon form of a matrix. Solving linear systems by Gauss-Jordan reduction. Finding the inverse of a matrix by row reduction. Equivalent matrices. Determinants. Properties of determinants. Cofactor expansion. Inverse of a matrix (via its determinant). Other applications of determinants (Cramers rule). Vectors in the plane and in 3-space. Vector spaces. Subspaces. Span and linear independence. Basis and dimension. Row space. Null space. Nullity and rank of a matrix. Homogeneos systems. Change of basis. Transition matrices. Orthogonalization. Linear transformations. Kernel and range of a linear transformation.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Prof. Ece YETKİN ÇELİKEL https://profil.hku.edu.tr/akademik/ece-yetkin-celikel/ ece.celikel@hku.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources DERS KİTAPLARI: Elementary Linear Algebra with Applications, 9 ed. B.Kolman, D.Hill, Person Inc. YARDIMCI KİTAPLAR: Elemantary Linear Algebra with Applications, 2nd ed., R.O.Hill, HBJ Pres.
Course Notes Elementary Linear Algebra with Applications, 9 ed. B.Kolman, D.Hill, Person Inc.
Elemantary Linear Algebra with Applications, 2nd ed., R.O.Hill, HBJ Pres.

Course Category
Mathematics and Basic Sciences %60
Engineering %30
Engineering Design %10

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 45
Final examination 1 % 55
Total
2
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 15 3 45
Hours for off-the-c.r.stud 15 7 105
Assignments 15 2 30
Mid-terms 1 2 2
Final examination 1 2 2
Total Work Load   Number of ECTS Credits 6 184

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 A comprehension of mathematics (algebra, differential, integration …) and fundamentals of science
2 Ability to apply knowledge of mathematics, science and engineering to problems in electronics engineering.
3 Ability to recognize the needs and challenges of our age and to assess the global and social impact of engineering solutions
4 Ability to identify, formulate and solve engineering problems.
5 Ability to effectively communicate knowledge and opinions via written, oral visual means.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Systems of Linear Equations
2 Gauss Elimination and Row Echelon Form
3 Matrices and Matrix Operations
4 Elementary Matrices and $LU$ Decomposition
5 Matrix Inverses and Arithmetic Rules
6 Determinant Concept and Properties
7 Cofactors and Cramer ` s Rule
8 Vector Spaces and Subspaces
9 Linear Dependence/Independence and Span
10 Basis and Dimension
11 Null Space, Column Space, and Rank
12 Inner Product Spaces and Orthogonality
13 Gram-Schmidt Process and QR Factorization
14 Eigenvalues and Eigenvectors
15 Diagonalization and Linear Transformations

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
C1 3 2
C2 3 2
C3 2 3 3
C4 2 3
C5 3 2

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant