Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
CMP5133 Artificial Neural Networks Fall 3 0 3 8
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: En
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi CEMAL OKAN ŞAKAR
Course Lecturer(s): Dr. Öğr. Üyesi CEMAL OKAN ŞAKAR
Course Objectives: The objective of this course is to introduce the fundamental artificial neural network architectures and algorithms. Students will also learn to use neural networks in order to solve real world problems.

Learning Outputs

The students who have succeeded in this course;
I. Explain the learning and generalization aspects of neural network systems.
II. Be able to apply backpropagation algorithm to a classification problem
III. Be able to apply support vector machines to a classification problem.
IV. Be able to implement self organizing maps.
V. Describe and explain the most common architectures and learning algorithms

Course Content

Perceptrons, linear regression, least mean squares algorithm, multi-layer perceptrons, backpropagation algorithm, support vector machines, radial basis function networks, self organizing maps, recurrent neural networks.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction
2) Perceptron
3) Linear regression
4) Least mean squares algorithm.
5) Multi-layer preceptrons.
6) Backpropagation algorithm.
7) Support vector machines
8) Support vector machines
9) Radial basis function networks.
10) Radial basis function networks
11) Self organizing maps
12) Self organizing maps
13) Recurrent neural networks
14) Recurrent neural networks


Course Notes: Neural Networks and Learning Machines By Simon Haykin Publisher: Prentice Hall; 3 edition
References: Yok - None

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance % 0
Laboratory % 0
Application % 0
Field Work % 0
Special Course Internship (Work Placement) % 0
Quizzes % 0
Homework Assignments 5 % 25
Presentation 1 % 10
Project 1 % 25
Seminar % 0
Midterms % 0
Preliminary Jury % 0
Final 1 % 40
Paper Submission % 0
Jury % 0
Bütünleme % 0
Total % 100
Total % 100

ECTS / Workload Table

Activities Number of Activities Workload
Course Hours 14 42
Special Course Internship (Work Placement)
Field Work
Study Hours Out of Class
Presentations / Seminar
Project 13 65
Homework Assignments 13 65
Preliminary Jury
Paper Submission
Final 5 19
Total Workload 191

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
Program Outcomes Level of Contribution
1) Gains an academic background and abilities for making scientific research; analysis, interpretation and application of knowledge in subjects of Mechatronics Engineering.
2) Acquires an ability to select, apply and develop modern techniques and methods for mechatronics engineering applications.
3) Develops new and innovative ideas, procedures and solutions in the design of mechatronics systems, components and processes.
4) Gains an ability for experimental design, data accumulation, data analysis, reporting and implementation.
5) Acquires abilities for individual and team-work, communication and collaboration with team members and interdisciplinary cooperation.
6) Gains an ability to communicate effectively oral and written; and a knowledge of English sufficient to follow technical developments and terminology.
7) Acquires recognition of the need for, and an ability to access and report knowledge, to engage in life-long learning.
8) Gains an understanding of universal, social and professional ethics.
9) Acquires a knowledge of business-oriented project organization and management; awareness of entrepreneurship, innovation and sustainable development
10) Gains awareness for the impact of mechatronics engineering applications on human health, environmental, security and legal issues in a global and social context.