ECTS - Linear Algebra
Linear Algebra (MATH275) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Linear Algebra | MATH275 | 3. Semester | 4 | 0 | 0 | 4 | 6 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Compulsory Departmental Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Question and Answer, Drill and Practice. |
Course Lecturer(s) |
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Course Objectives | This course is designed to enrich the knowledge of engineering students in linear algebra, and to teach them the basics and application of the methods for the solution of linear systems occurring in engineering problems. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Linear equations and matrices, real vector spaces, inner product spaces, linear transformations and matrices, determinants, eigenvalues and eigenvectors. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Systems of Linear Equations, Matrices, Matrix Multiplication, Algebraic Properties of Matrix Operations | pp. 1-39 |
2 | Special Types of Matrices and Partitioned Matrices, Echelon Form of a Matrix, Solving Linear Systems | pp. 42-49, 86-93, 95-103, 111-113 |
3 | Elementary Matrices; Finding Inverses, Equivalent Matrices | pp. 117-124, 126-129 |
4 | Determinants, Properties of Determinants, Cofactor Expansion | pp. 141-145, 146-154, 157-163 |
5 | Inverse of a Matrix (via Its Determinant), Other Applications of Determinants (Cramer’s Rule) | pp. 165-168, 169-172 |
6 | Vectors in the Plane and In 3-D Space, Vector Spaces, Subspaces | pp. 177-186, 188-196, 197-203 |
7 | Span, Linear Independence, Basis and Dimension | pp. 209-214, 216-226, 229-241 |
8 | Homogeneous Systems, Coordinates and Isomorphism, Rank of a Matrix | pp. 244-250, 253-266, 270-281 |
9 | Inner Product Spaces, Gram-Schmidt Process | pp. 290-296, 307-317, 320-329 |
10 | Orthogonal Complements, Linear Transformations and Matrices | pp. 332-343, 363-372 |
11 | Kernel and Range of a Linear Transformation | pp. 375-387 |
12 | Matrix of a Linear Transformation | pp. 389-397 |
13 | Eigenvalues and Eigenvectors | pp. 436-449 |
14 | Diagonalization and Similar Matrices, Diagonalization of Symmetric Matrices | pp. 453-461, 463-472 |
15 | General Review | |
16 | Final Exam |
Sources
Course Book | 1. Elementary Linear Algebra, B. Kolman and D.R. Hill, 9th Edition, Prentice Hall, New Jersey, 2008 |
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Other Sources | 2. Linear Algebra, S. H. Friedberg, A. J. Insel, L. E. Spence, Prentice Hall, New Jersey, 1979 |
3. Basic Linear Algebra, Cemal Koç, Matematik Vakfı Yay., Ankara, 1996 |
Evaluation System
Requirements | Number | Percentage of Grade |
---|---|---|
Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | - | - |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 60 |
Final Exam/Final Jury | 1 | 40 |
Toplam | 3 | 100 |
Percentage of Semester Work | 60 |
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Percentage of Final Work | 40 |
Total | 100 |
Course Category
Core Courses | |
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Major Area Courses | |
Supportive Courses | X |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Adequate knowledge in mathematics, science and computing fields; ability to apply theoretical and practical knowledge of these fields in solving engineering problems related to information systems. | X | ||||
2 | Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | X | ||||
3 | Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose. | |||||
4 | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in information systems engineering applications; ability to use information technologies effectively. | |||||
5 | Ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the information systems discipline. | |||||
6 | Ability to work effectively in inter/inner disciplinary teams; ability to work individually. | |||||
7 | a. Effective oral and written communication skills in Turkish; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. b. Knowledge of at least one foreign language; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
8 | Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development. | |||||
9 | a. Ability to behave according to ethical principles, awareness of professional and ethical responsibility. b. Knowledge of the standards utilized in information systems engineering applications. | |||||
10 | a. Knowledge on business practices such as project management, risk management and change management. b. Awareness about entrepreneurship, and innovation. c. Knowledge on sustainable development. | |||||
11 | a. Knowledge of the effects of information systems engineering applications on the universal and social dimensions of health, environment, and safety. b. Awareness of the legal consequences of engineering solutions. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | |||
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 14 | 4 | 56 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | |||
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 10 | 20 |
Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
Total Workload | 86 |