• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. Explain solution techniques for linear systems

   Contribution to Program Outcomes

   1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
   2. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
   3. Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.

   Method of assessment

   1. Written exam
2. Interpret mathematical concept of linear independence

   Contribution to Program Outcomes

   1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.

   Method of assessment

   1. Written exam
3. Define a vector spaces

   Contribution to Program Outcomes

   1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
   2. Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.
   3. Exhibiting professional and ethical responsibility.

   Method of assessment

   1. Written exam
4. Recognize and hopefully adapt at simple proof techniques

   Contribution to Program Outcomes

   1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
   2. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
   3. Exhibiting professional and ethical responsibility.

   Method of assessment

   1. Written exam

Contents
Week 1:	Systems of linear equations and matrices
Week 2:	Properties of matrices, echelon form of a matrix
Week 3:	Solving linear systems
Week 4:	Elementary matrices, inverses and equivalent matrices
Week 5:	Determinants
Week 6:	Applications of determinants
Week 7:	Vectors in R^2 and R^2, properties
Week 8:	Midterm exam
Week 9:	Vector spaces and subspaces
Week 10:	Span
Week 11:	Linear independence
Week 12:	Basis and dimension
Week 13:	Coordinates and isomorphisms
Week 14:	Ranks
Week 15*:	-
Week 16*:	Final exam
Textbooks and materials:	Elementary Lineer Algebra, 7th Ed. Bernard Kolman ve David R. Hill
Recommended readings:	-
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	8	40
Other in-term studies:		0
Project:		0
Homework:		0
Quiz:		0
Final exam:	16	60
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	14
Own studies outside class:	3	14
Practice, Recitation:	2	14
Homework:	0	0
Term project:	0	0
Term project presentation:	0	0
Quiz:	0	0
Own study for mid-term exam:	15	1
Mid-term:	2	1
Personal studies for final exam:	15	1
Final exam:	2	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)