| Semester | Course Unit Code | Course Unit Title | T+P+L | Credit | Number of ECTS Credits |
| 1 | ECE560 | ARTIFICIAL NEURAL NETWORKS | 3+0+0 | 3 | 7,5 |
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Language of Instruction
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English
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Level of Course Unit
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Master's Degree
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Department / Program
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ELECTRICAL AND COMPUTER ENGINEERING
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Type of Program
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Formal Education
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Type of Course Unit
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Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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Gain an understanding of neural network models
Learn the techniques used for developing neural network models
Gain practice by implementing neural network models
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Course Content
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This course provides an introduction to neural networks. It covers perceptrons, single and multi-layer networks, network training, regularization, and ensembles. Mathematical principles will be explained to provide a solid foundation for neural networks. Methods will be implemented by a software and applied on various machine learning problems.
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Course Methods and Techniques
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Prerequisites and co-requisities
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None
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Course Coordinator
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None
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Name of Lecturers
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None
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Assistants
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None
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Work Placement(s)
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No
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Recommended or Required Reading
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Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
ECTS Allocated Based on Student Workload
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
Weekly Detailed Course Contents
Contribution of Learning Outcomes to Programme Outcomes
Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant
https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=77741&lang=en