Information Systems Engineering | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | FEC207 | ||||||||
Ders İsmi: | Linear Algebra | ||||||||
Ders Yarıyılı: | Fall | ||||||||
Ders Kredileri: |
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Language of instruction: | Turkish | ||||||||
Ders Koşulu: | |||||||||
Ders İş Deneyimini Gerektiriyor mu?: | Yes | ||||||||
Type of course: | Required | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Assoc. Prof. Dr. MERVE TEMİZER ERSOY | ||||||||
Course Lecturer(s): |
Asst. Prof. Dr. MELİSA RAHEBİ Prof. Dr. İLKE TAŞCIOĞLU |
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Course Assistants: |
Course Objectives: | To learn the basics of Linear Algebra and to use this knowledge in solving engineering problems. |
Course Content: | In this course, the general concepts of linear algebra are examined under the following topics: Systems of linear equations and matrices, Gaussian elimination method, matrix algebra, inverse of a matrix, elementary matrices, LU decomposition, determinant of a square matrix, properties of determinant, Cramer's rule, vector spaces, sub-spaces. spaces, linear independence, basis and dimension, base change, inner product spaces, orthonormal basis, linear transformations, matrix representation of linear transformation, eigenvalues and eigenvectors, diagonalization. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | Matrices and systems of linear equations | Lecture Notes |
2) | Matrices and systems of linear equations | Lecture Notes |
3) | Matrices and systems of linear equations | Lecture Notes |
4) | Matrices and systems of linear equations | Lecture Notes |
5) | Determinants | Lecture Notes |
6) | Determinants | Lecture Notes |
7) | Vector spaces | Lecture Notes |
8) | Mid term | Lecture Notes |
9) | Vector spaces | Lecture Notes |
10) | Inner product spaces | Lecture Notes |
11) | Linear transformations | Lecture Notes |
12) | Linear transformations | Lecture Notes |
13) | Eigenvalues and eigenvectors | Lecture Notes |
14) | Eigenvalues and eigenvectors | Lecture Notes |
15) | Final | Lecture Notes |
Course Notes / Textbooks: | Linear Algebra and Its Applications, 5th edition/Global edition, David C. Lay et al., Pearson, 2016. Elementary Linear Algebra, Cengage Learning, 7th or 8th edition, Ron Larson, (e-book or hardcopy). |
References: | 1. Linear Algebra By MIT Open Courseware 2. Coding The Matrix By Philip Klein 3. Linear Algebra for Machine Learning By Applied AI Course 4. Deep Learning Book By Ian Goodfellow and Yoshua Bengio and Aaron Courville 5. Computational Linear Algebra for Coders By fast.ai 6. Basic Linear Algebra for Deep Learning By Niklas Donges 7. Linear Algebra By Khan Academy |
Ders Öğrenme Kazanımları | 1 |
2 |
4 |
3 |
5 |
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Program Outcomes |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |
Semester Requirements | Number of Activities | Level of Contribution |
Midterms | 1 | % 50 |
Final | 1 | % 50 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 50 | |
PERCENTAGE OF FINAL WORK | % 50 | |
total | % 100 |