Course Name  Linear Algebra II 
Code  Semester  Theory (hour/week)  Application/Lab (hour/week)  Local Credits  ECTS 

MATH 106  Spring  2  2  3  6 
Prerequisites 
 
Course Language  English  
Course Type  Required  
Course Level  First Cycle  
Mode of Delivery    
Teaching Methods and Techniques of the Course  
Course Coordinator    
Course Lecturer(s)  
Assistant(s)   
Course Objectives  Linear Algebra II course is theoretic course, which deals with linear vector spaces and fundamental theories related with these spaces. The scope of this course is to derive different algebraic techniques and to utilize these techniques in a variety of mathematical areas. 
Learning Outcomes  The students who succeeded in this course;

Course Description  In this course, the concepts of bases, dimensions, linear transformations, orthogonality, inner product spaces, eigenvalues, eigenvectors and diagonalization are discussed. 
 Core Courses  X 
Major Area Courses  
Supportive Courses  
Media and Managment Skills Courses  
Transferable Skill Courses 
Week  Subjects  Required Materials 
1  Vector spaces and subspaces  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 4.1. 
2  Null spaces, column spaces and linear transformations  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 4.2. 
3  Linearly independent sets, bases  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 4.3. 
4  Coordinate systems  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 4.4. 
5  The dimension of a vector space, rank  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 4.5, 4.6. 
6  Change of basis  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 4.7. 
7  Eigenvectors and eigenvalues  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 5.1, 5.2. 
8  Diagonalization  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 5.3. 
9  Eigenvectors and linear transformations  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 5.4. 
10  Inner product, length and orthogonality  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 6.1. 
11  Orthogonal sets  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 6.2. 
12  Orthogonal projections  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 6.3. 
13  The GramSchmidt process  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 6.4. 
14  Least squares problems  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. Section 6.5. 
15  Review of semester.  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. 
16  Review of semester.  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. 
Course Notes/Textbooks  "Linear Algebra and Its Applications" by David C.Lay, Stephan R.Lay and Judi J. McDonald, Pearson, Global Edition. 
Suggested Readings/Materials  “Introductory Linear Algebra with applications” by Bernard Kolman, David R. Hill. Prentice Hall, 9th edition. 
Semester Activities  Number  Weigthing 
Participation  
Laboratory / Application  
Field Work  
Quizzes / Studio Critiques  
Portfolio  
Homework / Assignments  
Presentation / Jury  
Project  
Seminar / Workshop  
Oral Exam  
Midterm  2  60 
Final Exam  1  40 
Total 
Weighting of Semester Activities on the Final Grade  2  60 
Weighting of EndofSemester Activities on the Final Grade  1  40 
Total 
Semester Activities  Number  Duration (Hours)  Workload 

Course Hours (Including exam week: 16 x total hours)  16  4  64 
Laboratory / Application Hours (Including exam week: 16 x total hours)  16  
Study Hours Out of Class  16  4  
Field Work  
Quizzes / Studio Critiques  
Portfolio  
Homework / Assignments  
Presentation / Jury  
Project  
Seminar / Workshop  
Oral Exam  
Midterms  2  9  
Final Exams  1  19  
Total  165 
#  Program Competencies/Outcomes  * Contribution Level  
1  2  3  4  5  
1  To have a grasp of basic mathematics, applied mathematics and theories and applications of statistics.  X  
2  To be able to use theoretical and applied knowledge acquired in the advanced fields of mathematics and statistics,  X  
3  To be able to define and analyze problems and to find solutions based on scientific methods,  X  
4  To be able to apply mathematics and statistics in real life with interdisciplinary approach and to discover their potentials,  X  
5  To be able to acquire necessary information and to make modeling in any field that mathematics is used and to improve herself/himself,  X  
6  To be able to criticize and renew her/his own models and solutions,  X  
7  To be able to tell theoretical and technical information easily to both experts in detail and nonexperts in basic and comprehensible way,  X  
8  To be able to use international resources in English and in a second foreign language from the European Language Portfolio (at the level of B1) effectively and to keep knowledge uptodate, to communicate comfortably with colleagues from Turkey and other countries, to follow periodic literature,  X  
9  To be familiar with computer programs used in the fields of mathematics and statistics and to be able to use at least one of them effectively at the European Computer Driving Licence Advanced Level,  
10  To be able to behave in accordance with social, scientific and ethical values in each step of the projects involved and to be able to introduce and apply projects in terms of civic engagement,  
11  To be able to evaluate all processes effectively and to have enough awareness about quality management by being conscious and having intellectual background in the universal sense,  X  
12  By having a way of abstract thinking, to be able to connect concrete events and to transfer solutions, to be able to design experiments, collect data, and analyze results by scientific methods and to interfere,  X  
13  To be able to continue lifelong learning by renewing the knowledge, the abilities and the compentencies which have been developed during the program, and being conscious about lifelong learning,  
14  To be able to adapt and transfer the knowledge gained in the areas of mathematics and statistics to the level of secondary school,  X  
15  To be able to conduct a research either as an individual or as a team member, and to be effective in each related step of the project, to take role in the decision process, to plan and manage the project by using time effectively. 
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest