TYPE OF COURSE UNIT	Compulsory Course
LEVEL OF COURSE UNIT	Bachelor's Degree
YEAR OF STUDY	2
SEMESTER	Third Term (Fall)
NUMBER OF ECTS CREDITS ALLOCATED	4
NAME OF LECTURER(S)	Associate Professor Müjdat Kaya
LEARNING OUTCOMES OF THE COURSE UNIT	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) Solidify the patterns of rational or mathematical (and therefore exact) thinking. 3) Have a knowledge with the Engineering Mathematics needed in diverse areas of science and technology in general, and specific areas of engineering in particular. 4) Acquire effective analytical thinking ability and study habits; and also deepen and widen his thought and vision. 5) Develop problem-solving skills. 6) Will be able to apply the Engineering Mathematics knowledge for solving science and engineering problems. 7) Acquire the ability of keeping up with the constantly changing science, technology and engineering methods.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	Yes(MAT152)
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, n-space Rn , Scalar(dot) product, Equations of Line and Plane, System of Linear Equations and Solutions 2nd Week Gaussian Elimination Method 3rd Week Matrices, Transpoze of Matrix, Inverse of Matrix and Properties 4th Week Applications of Matrices, Determinants, Properties of Determinants, Eigenvalues of Matrices 5th Week Cross Product, Scalar Triple Product and Properties 6th Week The vector spaces R2, R3, Rn and Norm of a Vector, Lines and Planes 7th Week General Vector Spaces, Subspaces,Linear Dependence, Linear Independence, Spanning, Basis and Dimension 8th Week Midterm Exam 9th Week Inner Product Spaces, Orthonormal Bases, Gram-Schmidt Process, Linear Transformations 10th Week Kernel and Range Spaces, Rank and Nullity, Inverse Linear Transformations 11th Week Diagonalization, Change of Bases 12th Week Matrices of Linear Transformation, Eigenvalues and Eigenvectors 13th Week Similarity, Jordan Canonical Form, Quadratic Forms 14th Week Complex Vector Spaces, Complex Inner Product Spaces, Complex Matrices, Unitary, Normal, and Hermitian Matrices
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 30 Quiz 2 20 Attendance 1 10 Total(%) 60 Contribution of In-term Studies to Overall Grade(%) 60 Contribution of Final Examination to Overall Grade(%) 40 Total(%) 100
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No