Semester  Course Unit Code  Course Unit Title  L+P  Credit  Number of ECTS Credits 
4  MATH262  LINEAR ALGEBRA II  3+2  4  6 
Language of Instruction

English

Level of Course Unit

First Cycle

Department / Program

MATHEMATICS

Mode of Delivery

Face to Face

Type of Course Unit

Compulsory

Objectives of the Course

To introduce students with basic concepts related with the abstract spaces and linear operators. To teach the spectral properties of some special matrices. To show the use of theoretical knowledge in solving some applied problems. To give elementary background for more advanced study in linear algebra. To motivate students to do research and use different literature when learning the course

Course Content

Inner Product Spaces. Orthınormal Bases. Orthogonal Projections. GramShmidt Process. Best Approximation. Least Squares. Orthogonal Matrices. Orthogonal Diagonalization. Real Quadratic Forms. Optimization Using Quadratic Forms. Hermitian, Normal, and Unitary Matrices. Unitary Diagonalization. General Linear Transformations. Matrix Representation of Linear Transformations. Singular Value Decomposition. Polar Decomposition. Linear Programming. Selected Applications.

Course Methods and Techniques


Prerequisites and corequisities

None

Course Coordinator

None

Name of Lecturers

Prof.Dr. Şirin ATILGAN BÜYÜKAŞIK

Assistants

None

Work Placement(s)

No

Recommended or Required Reading
Resources

"Elementary Linear Algebra", Applications Version, H. Anton, C. Rorres, A. Kaul, 12th Edition, Wiley.










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
InTerm Studies

Midterm exams

2

%
50

Quizzes

3

%
10

Homeworks

0

%
0

Other activities

0

%
0

Laboratory works

0

%
0

Projects

0

%
0

Final examination

1

%
40

Total

6

%
100

ECTS Allocated Based on Student Workload
Activities

Total Work Load

Weekly Course Time

1

52

52

Outside Activities About Course (Attendance, Presentation, Midterm exam,Final exam, Quiz etc.)

1

64

64

Exams and Exam Preparations

1

64

64

Total Work Load
 

Number of ECTS Credits 6
180

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
No  Learning Outcomes 
1
 to have knowledge about inner product spaces 
2
 to be able to fing orthogonal basis and use it in problem solving 
3
 to be able to solve problems related to special matrices 
4
 to have knowledge about linear transformations 
5
 to be able to use theoretical knowledge for solving problems 
Weekly Detailed Course Contents
Week  Topics  Study Materials  Materials 
1 
Inner Product Spaces, Orthonormal Basis.


Chapter 6.1 and 6.2

2 
Orthogonal Projections. GramSchmidt Process.


Chapter 6.3

3 
Best Approximation. Least Squares


Chapter 6.4

4 
Orthogonal Matrices. Orthogonal Diagonalization.


Chapter 7.1 and 7.2

5 
Real Quadratic Forms


Chapter 7.3

6 
Optimization Using Quadratic Forms


Chapter 7.4

7 
Hermitian, Normal and Unitary Matrices. Unitary Diagonalization.


Chapter 7.5

8 
General Linear Transformations


Chapter 8.1 and 8.2

9 
Matrix Representation of Linear Transformations


Chapter 8.3, 8.4, 8.5

10 
Singular Value Decomposition


Chapter 9.4 ve 9.5

11 
Polar Decomposition


Chapter 9.4 ve 9.5

12 
Linear Programming



13 
Simplex Method



14 
Applications



15 
Final 1st week



16 
Final 2nd week



Contribution of Learning Outcomes to Programme Outcomes
Contribution: 0: Null 1:Slight 2:Moderate 3:Significant 4:Very Significant
https://obs.iyte.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=168143&lang=en