ELECTRIC-ELECTRONIC ENGINEERING (ENGLISH, NON-THESIS) | |||||
Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
CMP5133 | Artificial Neural Networks | Fall Spring |
3 | 0 | 3 | 12 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
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 |
Recommended Optional Program Components: | None |
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. |
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 |
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. |
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 / Textbooks: | Neural Networks and Learning Machines By Simon Haykin Publisher: Prentice Hall; 3 edition |
References: | Yok - None |
Semester Requirements | Number of Activities | Level of Contribution |
Homework Assignments | 5 | % 25 |
Presentation | 1 | % 10 |
Project | 1 | % 25 |
Final | 1 | % 40 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 35 | |
PERCENTAGE OF FINAL WORK | % 65 | |
Total | % 100 |
Activities | Number of Activities | Workload |
Course Hours | 14 | 42 |
Project | 13 | 65 |
Homework Assignments | 13 | 65 |
Final | 5 | 19 |
Total Workload | 191 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Have sufficient background and an ability to apply knowledge of mathematics, science, and engineering to identify, formulate, and solve problems of electrical and electronics engineering. | |
2) | Be able to define, formulate and solve sophisticated engineering problems by choosing and applying appropriate analysis and modeling techniques and using technical symbols and drawings of electrical and electronics engineering for design, application and communication effectively. | |
3) | Have an ability to design or implement an existing design of a system, component, or process to meet desired needs within realistic constraints (realistic constraints may include economic, environmental, social, political, health and safety, manufacturability, and sustainability issues depending on the nature of the specific design). | |
4) | Elektrik ve elektronik mühendisliği yapabilmek ve yeni uygulamalara uyum gösterebilmek için gerekli yenilikçi ve güncel teknikler, beceriler, bilgi teknolojileri ve modern mühendislik araçlarını geliştirmek, seçmek, uyarlamak ve kullanmak. | |
5) | Be able to design and conduct experiments, as well as to collect, analyze, and interpret relevant data, and use this information to improve designs. | |
6) | Be able to function individually as well as to collaborate with others in multidisciplinary teams. | |
7) | Be able to communicate effectively in English and Turkish (if he/she is a Turkish citizen). | |
8) | Be able to recognize the need for, and to engage in life-long learning as well as a capacity to adapt to changes in the technological environment. | |
9) | Have a consciousness of professional and ethical responsibilities as well as workers’ health, environment and work safety. | |
10) | Have the knowledge of business practices such as project, risk, management and an awareness of entrepreneurship, innovativeness, and sustainable development. | |
11) | Have the broad knowledge necessary to understand the impact of electrical and electronics engineering solutions in a global, economic, environmental, legal, and societal context. |