Course Details

LINEAR ALGEBRA FOR ELECTRICAL-ELECTRONICS ENGINEERS

MATH103

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Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1MATH103LINEAR ALGEBRA FOR ELECTRICAL-ELECTRONICS ENGINEERS4+0+044

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program ELECTRICAL-ELECTRONICS ENGINEERING
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course Numerous engineering problems are represented by vectors and matrices. For example, in robotics, derivation of kinematics for mechatronic systems requires to solve matrix operations. Many optimization objectives are expressed as linear inequalities, which requires a fundamental understanding of linear algebra. Similarly, some computer vision and graph theory applications build upon linear algebra. This course aims to help you gain essential theoretical and programming skills which you can further apply in various fields.

Particularly, the main goals of the course are as follows:
• Developing a theoretical background on vectors and matrix algebra.
• Providing fundamental solution methods for systems of linear equations.
• Providing necessary programming knowledge for applying matrix algebra on MATLAB.
Course Content The course covers the basic framework for vector and matrix operations. Topics include vectors, matrices, solution methods for systems of linear equations, vector spaces, orthogonality, eigenvalues and eigenvectors, and singular value decomposition.
Course Methods and Techniques In this course, theoretical knowledge is provided first, followed by problem-solving to reinforce the material.
Prerequisites and co-requisities None
Course Coordinator Associate Prof.Dr. GÜNYAZ ABLAY gunyaz.ablay@agu.edu.tr
Name of Lecturers None
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources
Introduction to Vectors and Matrices
Solving Linear Equations: Part I
Solving Linear Equations: Part II
Solving Linear Equations: Part III
Introduction to Vector Spaces
Independence, Basis and Dimension
Orthogonality and Least Squares Approximation
Lecture Free Week - Recitation
Orthogonal Bases and Gram-Schmidt
Introduction to Eigenvalues
Eigenvalues and Eigenvectors
Singular Value Decomposition
Application Examples
Review
https://math.mit.edu/~gs/linearalgebra/

Course Category
Mathematics and Basic Sciences %90
Engineering %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
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı 1 % 20
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı 2 % 15
Quiz/Küçük Sınav 4 % 40
Final examination 1 % 25
Total
8
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Tartışma 1 1 1
Yazılı Sınav 5 6 30
Grup Projesi 2 7 14
Teslim İçin Hazırlık 2 5 10
Rapor 2 3 6
Yüz Yüze Ders 56 1 56
Der Dışı Final Sınavı 1 3 3
Total Work Load   Number of ECTS Credits 4 120

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Demonstrate essential understanding of vector spaces and matrix algebra.
2 Formulate given real-world problems as systems of linear equations and apply matrix algebra in reaching a solution.
3 Design and implement matrix algebra in MATLAB through embedded functions and custom scripts.
4 Find out the connection between processes on linear conversions and their related matrices.


Weekly Detailed Course Contents
Veri yok


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1
C2
C3
C4

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


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=74382&lang=en
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