TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF SCIENCE AND LETTERS |
| ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING PR. (ENGLISH) | |
| Code | YZZ105 |
| Name | Linear Algebra |
| Term | 2025-2026 Academic Year |
| Semester | 1. Semester |
| Duration (T+A) | 3-1 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3.5 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Label | BS Basic Science Courses C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. GÜZİN YÜKSEL |
| Course Instructor |
Dr. Öğr. Üyesi Emrah KORKMAZ
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The aim of this course is to provide knowledge and skills regarding the concrete aspects of linear algebra in the research process.
Course Content
Matrices and Homogeneous, Linear Equation Systems, solving systems with the help of matrices, understanding vector spaces and abstract mathematical expressions constitute the content of this course.
Course Precondition
None
Resources
Bernard Kolman, David R. Hill, Lineer Cebir (Çeviri ) Palme Yayıncılık,2000.
Notes
Arif Sabuncuoğlu, Lineer Cebir, Nobel yayın dağıtım,2000.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Distinguish between matrices and matrix operations. |
| LO02 | It brings matrices into echelon form by Gaussian Elimination and Gauss-Jordan Reduction. |
| LO03 | It uses the inverse of the matrix to solve systems. |
| LO04 | Determinant calculations. |
| LO05 | Solve systems using Cramer's rule. |
| LO06 | Can draw vectors on the plane and in space and perform vector operations. |
| LO07 | Uses the basic concepts of Vector Spaces. |
| LO08 | Writes the linear spacing space. |
| LO09 | Determines linear dependence and independence of vectors. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | It provides a broad range of knowledge about fundamental Computer Science concepts, algorithms and data structures. | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Learns basic computer topics such as software development, programming languages, and database management. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Understands advanced computing fields such as data science, artificial intelligence, and machine learning. | |
| PLO04 | Belirsiz | Learn about topics such as computer networks, cyber security, and database design. | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Develops skills in designing, implementing and analyzing algorithms. | 4 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Gains the ability to use different programming languages effectively | |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Learns data analysis, database management and big data processing skills. | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Gains practical experience by working on software development projects. | |
| PLO09 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Strengthens collaboration and communication skills within the team. | |
| PLO10 | Yetkinlikler - Alana Özgü Yetkinlik | It provides a mindset open to technological innovations. | 3 |
| PLO11 | Yetkinlikler - Öğrenme Yetkinliği | Encourages continuous learning and self-improvement competence. | 4 |
| PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Develops the ability to solve complex problems. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Systems of Linear Equations | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 2 | Matrices and matrix operations | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 3 | Properties of matrix operations and special types of matrices | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 4 | Echelon form of a matrix and Elementary matrices | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 5 | Gauss Jordan and Gaussian Reduction Method | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 6 | Finding the inverse of a matrix and solving the system | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 7 | Determinant function and its properties | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 8 | Mid-Term Exam | Repetition of the topics covered from lecture notes and resources | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Solution of Cramer systems using determinants | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 10 | Vectors in the Plane and in Space | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 11 | Vector Spaces | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 12 | Subspaces | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 13 | Linear Spatial | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 14 | Linear dependence and independence | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 15 | Problem Solving, final exam | Reading relevant sections of course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 16 | Term Exams | Repetition of the topics covered from lecture notes and resources | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Repetition of the topics covered from lecture notes and resources | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 4 | 56 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 26 | 26 |
| Total Workload (Hour) | 136 | ||
| Total Workload / 25 (h) | 5,44 | ||
| ECTS | 5 ECTS | ||