| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Linear Algebra | TKN203 | Compulsory | Bachelor's degree | 2 | Fall | 3 |
Name of Lecturer(s)
Associate Prof. Dr. Arzu AKGÜL
Associate Prof. Dr. Sezgin BÜYÜKKÜTÜK
Associate Prof. Dr. Selda ÇALKAVUR
Associate Prof. Dr. Hakan KÖYLÜ
Learning Outcomes of the Course Unit
1) Knows matrix types and makes matrix operations
2) Transforms linear equation systems into matrix
form and solves the systems.
3) Determines eigenvalues and eigenvectors of
matrix
4) Knows vector and vector space and makes
operations
5) Determines linear independence in vectors
6) Determines similar and equivalent matrix of a
matrix
7) Knows orthogonal matrix and orthogonalizes a
matrix
8) Determines special matrices
9) Transforms quadratic functions into matrix form
and knows matrix functions and understands the
properties
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
| Learning Outcomes | ||||||||||||
| 1 | High | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 2 | No relation | Middle | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 3 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 4 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 5 | High | Middle | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 6 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 7 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 8 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 9 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
Matrices: Definition of matrix, Types of matrices, operations in matrices, Elementary row and column operations in matrices, Reduced row–echelon form, Rank of a matrix, the inverse of a square matrix with additional matrix, the inverse of a square matrix with unit matrix (Gauss Jordan method). Determinants: The determinant of a square matrix, properties of determinants, Sarrus rule. Linear Equation Systems: Solving systems of linear equations with the aid of equivalent matrices, Linear homogeneous equations, Cramer's method. Vectors: Vector definition, the sum and difference of vectors, the analytical expression vectors, scalar product of vectors, properties of the scalar multiplication, properties of scalar product, the mixed multiplication and properties, and properties of double vector product, Vector spaces: Definition of vector spaces and theorems. Subspaces. Span concept and fundamental theorems. Linear dependence and linear independence of vectors and some theorems about linear dependence and linear independence, bases and dimension concepts and fundamental theorems. Special matrix operations: Finding methods of similar matrix (Jordan canonical form), definition and norm of a matrix, orthogonality in matrices and orthogonalization of matrices ((Gram-Schmidt method), definition of coordinates and transition matrices and some theorems, calculation of eigenvalues and eigenvectors of a square matrix, the calculation of Inverse and power of a square matrix with the help of the Cayley-Hamilton theorem, transforming of quadratic function into matrix form, diagonalization of a matrix, matrix functions. Basics of MATLAB and matrix operations in MATLAB.
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Language of Instruction
Turkish
Work Placement(s)
Not Required