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| MAT1016 | Linear Algebra | 4+0+0 | ECTS:6 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of PHYSICS | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 4 hours of lectures per week | | Lecturer | Doç. Dr. Gül Deniz ÇAYLI | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | This course introduces fundamental concepts of linear algebra which are indispensable in all branches of basic sciences. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Analyse linear systems and determine their solution or solutions, if possible | 1,2,3,4 | 1, | | LO - 2 : | determine the best approximate solution in case the system fails to have a solution | 1,2,3,4 | 1 | | LO - 3 : | have knowlege and develop skills to handle problems on vector spaces and their subspaces | 1,2,3,4 | 1 | | LO - 4 : | observe that the best approximate solution that one seeks in approximation problems is obtained thorough the orthogonal projections | 1,2,3,4 | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Vectors in R^n ( Definition of Vectors, Vector Addition and scalar multiplication, Dot (inner) Product, Norm of a vector, distance between vectors, angle between of vectors, orthogonality), Matrix algebra (Basic concepts of vectors and Algebraic operations), Some Special Matrices and their properties Elemantary row operations, row reduction and Echelon Forms, Determinants and its properties, The inverse of a matrix, Systems of Linear Equations and solution sets, Eigenvalues and eigenvectors, Vector Space (Linear Dependence and independence, Spanning Sets, Basis and Dimension), Linear Transformations, Matrix Representation of a Linear Operator.
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Vectors in R^n ( Definition of Vectors, Vector Addition and scalar multiplication, Dot (inner) Product) | | | Week 2 | Vectors in R^n (Norm of a vector, distance between vectors, angle between of vectors, orthogonality) | | | Week 3 | Matrix algebra (Basic concepts of vectors and Algebraic operations) | | | Week 4 | Some Special Matrices and their properties | | | Week 5 | Elemantary row operations, row reduction and Echelon Forms | | | Week 6 | Determinant and its properties | | | Week 7 | The inverse of a matrix | | | Week 8 | Systems of Linear Equations and solution sets | | | Week 9 | Mid-term | | | Week 10 | Systems of Linear Equations and solution sets | | | Week 11 | Eigenvalues and eigenvectors | | | Week 12 | Vector Space (Linear Dependence and independence, Spanning Sets) | | | Week 13 | Vector Space (Basis and Dimension) | | | Week 14 | Linear Transformations | | | Week 15 | Matrix Representation of a Linear Operator | | | Week 16 | End-of-term exam | | | |
| 1 | Lay, David C., 2003, Linear Algebra and its applications, Addison Wesley | | | |
| 1 | Seymour Lipschutz, Marc Lipson, 2013, Lineer Cebir, Nobel yayıncılık. | | | 2 | Bernard Kolman, David R. Hill (Çeviri Editörü: Prof. Dr. Ömer Akın), 2002, Uygulamalı Lineer Cebir, Palme Yayıncılık. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 07/04/2018 | 2 | 50 | | End-of-term exam | 16 | 28/05/2018 | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 4 | 14 | 56 | | Sınıf dışı çalışma | 2 | 14 | 28 | | Arasınav için hazırlık | 10 | 1 | 10 | | Arasınav | 2 | 1 | 2 | | Kısa sınav | 1 | 2 | 2 | | Dönem sonu sınavı için hazırlık | 15 | 1 | 15 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 115 |
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