At the end of this course, the students; 1) Increase the awareness of his mental potential and abilities; gain an ability to utilize a higher percentage the capacity of the mind via brain exercises. 2) Acquire effective analytical thinking ability and study habits; and also deepen and widen his thought and vision. 3) Develop problem-solving skills. 4) Becomes able to apply their knowledge of Engineering Mathematics to science and engineering problems. 5) Acquires basic information that can be set the decision model . 6) 7)
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
This course contains these concepts: R Space, Dot Product of Vectors, Projections, Equations of Line and Plane, Systems of Linear Equations and Solutions, Gauss-Jordan Elimination, Matrices, Transpose and Inverse of Matrix, Matrix Applications, Determinants and Properties, Eigenvalue of Matrices, Cross Product, Scalar Triple Product, Norm, General Vector Spaces, Subspaces, Linear Dependence and Independence, Span, Basis and Dimension, Inner Product Spaces, Gram-Schmidt Orthogonalization Process, Linear Transformations, Kernel and Range, Rank and Nullity, Matrices of Linear Transformations, Eigenvectors of Linear Transform, Diagonalization, Change of Basis, Similarity, Jordan Canonical Form, Quadratic Surfaces, Complex Vector Spaces, Complex Matrices.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Introduction, System of Linear Equations and Solutions
2nd Week
Gauss Jordan Elimination Method
3rd Week
Matrices and Their Properties
4th Week
Determinats and Their Properties
5th Week
Cross Product, Scalar Triple Product and Properties. Lines and Planes. The Vector Spaces R2, R3, Rn and Norm of a Vector.
6th Week
General Vector Spaces, Subspaces
7th Week
Linear Dependence, Linear Independence, Spanning, Basis and Dimension
8th Week
Midterm Exam
9th Week
Inner Product Spaces, Gram-Schmidt Process
10th Week
Linear Transformations
11th Week
Kernel and Range Spaces, Rank and Nullity, Inverse Linear Transformations
12th Week
Eigenvalues and Eigenvectors
13th Week
Diagonalization, Change of Bases
14th Week
Quadratic Forms, Quadratic Surfaces
RECOMENDED OR REQUIRED READING
Howard Anton, Chris Rovves, Elementary Linear Algebra, Applications Version (1994), John Wiley&Sons. David C. Lay, Linear Algebra and Its Applications (2000), Addison - Wesley.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Questions/Answers
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
35
Quiz
2
15
Total(%)
50
Contribution of In-term Studies to Overall Grade(%)
50
Contribution of Final Examination to Overall Grade(%)
50
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
2
2
Preparation for Quiz
2
2
4
Individual or group work
13
2
26
Preparation for Final exam
1
16
16
Course hours
14
4
56
Preparation for Midterm exam
1
12
12
Laboratory (including preparation)
0
0
0
Final exam
1
2
2
Homework
0
0
0
Quiz
2
1
2
Total Workload
120
Total Workload / 30
4
ECTS Credits of the Course
4
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
