INTERNATIONAL BURCH UNIVERSITY
Graduate Study - Faculty of Engineering and Natural Sciences
3+2 Information Technology Master
2012-2013

SYLLABUS
Code Name Level Year Semester
CEN 591 Neural Networks Graduate 1 Fall
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
7.5 0 English

Instructor Assistant Coordinator
Günay Karli, Assoc. Prof. Dr. Günay Karli, Assoc. Prof. Dr.
[email protected] no email

COURSE OBJECTIVE

COURSE CONTENT
Week
Topic
  1. Introduction to The ANN and Biological Neuron Models
  2. Neuron Model and Network Architectures-Some Illustrative Examples
  3. Perceptron - its Structure and Learning Rules
  4. Adaline - The Adaptive Linear Element, its Structure and Learning Rules.
  5. Feedforward Multilayer Neural Networks
  6. Backpropagation algorithm.
  7. Applications of Multilayer Neural networks and Backpropagation
  8. Applications with MatLab
  9. Article Presentations
  10. Article Presentations
  11. Final Project Preparation
  12. Final Project Preparation
  13. Presentations of Final Project
  14. Presentations of Final Project

LABORATORY/PRACTICE PLAN
Week
Topic

    TEACHING/ASSESSMENT
    Description
    • Lectures
    • Project
    Description (%)
    Method Quantity Percentage (%)
    Homework120
    Midterm Exam(s)220
    Final Exam140
    Total: 80
    Learning outcomes
    • Demonstrate a systematic and critical understanding of the theories, principles and practices of computing;
    • Critically review the role of a “professional computing practitioner” with particular regard to an understanding of legal and ethical issues;
    • Creatively apply contemporary theories, processes and tools in the development and evaluation of solutions to problems and product design;
    • Actively participate in, reflect upon, and take responsibility for, personal learning and development, within a framework of lifelong learning and continued professional development;
    • Present issues and solutions in appropriate form to communicate effectively with peers and clients from specialist and non-specialist backgrounds;
    TEXTBOOK(S)
    • Hertz, John, Anders Krogh, and Richard G. Palmer. Introduction to the Theory of Neural Computation. Redwood City, CA: Addison-Wesley Pub. Co., 1991. ISBN: 9780201515602.
    • Koch, Christof. Biophysics of Computation: Information Processing in Single Neurons. New York, NY: Oxford University Press, 2004, ISBN: 9780195181999

    ECTS (Allocated based on student) WORKLOAD
    Activities Quantity Duration (Hour) Total Work Load
    Lecture (14 weeks x Lecture hours per week) 0
    Laboratory / Practice (14 weeks x Laboratory/Practice hours per week) 0
    Midterm Examination (1 week) 0
    Final Examination(1 week) 0
    Preparation for Midterm Examination 0
    Preparation for Final Examination7.50
    Total Workload: 0
    ECTS Credit (Total workload/25): 0