COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
YBS 456ARTIFICIAL NEURAL NETWORKS3 + 06th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective This course aims to give the basics of artificial neural network architectures and learning rules.
Course Content Definition of artificial neural networks (ANN) ADALINE: adaptive linear element, Learning: supervised and unsupervised learning Linear Associative Memory, Multi-layer perceptron Back-propagation method, Radial-basis ANN Dynamic ANN, Hopfield Network Cellular ANN.
Prerequisites No prerequisites.
Corequisite No corequisites.
Mode of Delivery Face to face

COURSE LEARNING OUTCOMES
1Learning articial neural networks
2Understanding the application areas
3Enhancing the subject area by a sample project on an application study

COURSE'S CONTRIBUTION TO PROGRAM
Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration14342
Hours for off-the-classroom study (Pre-study, practice)13339
Assignments11010
Mid-terms11313
Final examination12626
Total Work Load

ECTS Credit of the Course






130

5

COURSE DETAILS
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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes