COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Linear Algebra ENM   141 1 3 3 4

Prerequisites and co-requisites
Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Assoc.Prof.Dr. Dilek KAHYALAR
Instructors
Doç.Dr.DİLEK KAHYALAR1. Öğretim Grup:A
 
Assistants
Goals
The objectives of this course are to introduce the students with the basic ideas of linear algebra including vector spaces, subspaces, basis, dimension, linear transformations, matrices, systems of linear equations, eigenvalues and eigenvectors and to teach the understanding of abstract mathematical concepts and abstract thought arising from the concepts covered in this course.
Content
Vectors in the plane and space; vector spaces, subspaces, linear dependence, bases and finite dimensional vector spaces, linear transformations, matrices, representation of linear transformations by matrices, direct sum, systems of linear equations, determinants, characteristic vectors and diagonalization.

Learning Outcomes
1) Is able to prove Mathematical facts encountered in secondary school.
2) Recognizes the importance of basic notions in Algebra, Analysis and Topology
3) Develops maturity of mathematical reasoning and writes and develops mathematical proofs.
4) Is able to express basic theories of mathematics properly and correctly both written and verbally
5) Recognizes the relationship between different areas of Mathematics and ties between Mathematics and other disciplines.
6) Expresses clearly the relationship between objects while constructing a model
7) Draws mathematical models such as formulas, graphs and tables and explains them
8) Is able to mathematically reorganize, analyze and model problems encountered.
9) Knows at least one computer programming language
10) Uses effective scientific methods and appropriate technologies to solve problems
11) Knows programming techniques and is able to write a computer program
12) Is able to do mathematics both individually and in a group.
13)
14)
15)


Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Has sufficient background on topics related to mathematics, physical sciences and industrial engineering.
X
2
Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods.
X
3
Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems .
X
4
Gains ability to choose and apply methods and tools for industrial engineering applications.
X
5
Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions.
X
6
Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team.
X
7
Can access information and to search/use databases and other sources for information gathering.
X
8
Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously.
X
9
Can use computer software in industrial engineering along with information and communication technologies.
X
10
Can use oral and written communication efficiently.
X
11
Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession.
X
12
Has a conscious understanding of professional and ethical responsibilities.
X
13
Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice.
X
14
Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering.
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Vector space, subspace Required readings Lecture
Question-Answer
Discussion
Drilland Practice
2 Linear dependence, independence and a basis of a vector space Required readings Lecture
Question-Answer
Drilland Practice
3 Linear dependence, independence and a basis of a vector space Required readings Lecture
Question-Answer
Drilland Practice
4 Sum of subspaces, direct sum Required readings Lecture
Question-Answer
Drilland Practice
5 Linear transformations, their kernels and images Required readings Lecture
Question-Answer
Drilland Practice
6 The rank of a linear transformation, isomorphism Required readings Lecture
Question-Answer
Discussion
7 Matrices Required readings Lecture
Question-Answer
Discussion
8 Mid-term exam Review of the topics discussed in the lecture notes and sources Lecture
Question-Answer
Drilland Practice
Testing
9 Representation of linear transformations by matrices Required readings Lecture
Question-Answer
Discussion
Drilland Practice
10 The rank of a matrix, echelon matrix Required readings Lecture
Question-Answer
Discussion
Drilland Practice
11 Row equivalent matrices and systems of linear equations Required readings Lecture
Question-Answer
Drilland Practice
12 Determinant function, properties of determinant, evaluation of determinant Required readings Lecture
Question-Answer
Drilland Practice
13 Determinant function, properties of determinant, evaluation of determinant Required readings Lecture
Question-Answer
Discussion
14 Cramer Rule, eigen values and eigen vectors Required readings Lecture
Question-Answer
Drilland Practice
15 Characteristic spaces and characteristic polynomial Required readings Lecture
Question-Answer
Discussion
16-17 Final exam Review of the topics discussed in the lecture notes and sources Testing

Recommended or Required Reading
Textbook
Additional Resources