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ARTIFICIAL NEURAL NETWORKS COURSE IDENTIFICATION AND APPLICATION INFORMATION

Code Name of the Course Unit Semester In-Class Hours (T+P) Credit ECTS Credit
BIL422 ARTIFICIAL NEURAL NETWORKS 5 3 3 6

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY

Week Preparatory Topics(Subjects) Method
1 - Overview of Artificial Intelligence and Machine Learning -
2 - Introduction to Artificial Neural Networks -
3 - Structure and Basic Elements of Artificial Neural Networks -
4 - Early Artificial Neural Networks -
5 - Artificial Neural Network Model (Supervised Learning) Multilayer Perceptron -
6 - Artificial Neural Network Model (Supportive Learning) LVQ Model -
7 - Artificial Neural Network Model (Unsupervised Learning) Adaptive Resonance Theory (ART) Networks -
8 - MID-TERM EXAM -
9 - Recurrent Networks (Element Networks) and Other Artificial Neural Network Models -
10 - Hybrid Artificial Neural Networks -
11 - Hardware for Artificial Neural Networks -
12 - Overview of Applications of Artificial Neural Networks -
13 - Student Project Presentations -
14 - Student Project Presentations -
15 - ANN: General Overview -
16 - FINAL EXAM -
17 - FINAL EXAM -