Artificial neural networks (ANNs) as the subjects of artificial intelligence are widely used in computer science. ANNs are very advantageous in most systems, especially in the systems which have very complex mathematical structures. In this course, the aim is to teach ANN subjects in detail and to develop advanced ANN applications.

Introduction to Artificial Intelligence and Machine Learning. Introduction to Artificial Neural Networks (ANNs). The basic structures of ANNs. Elementary Artificial Neural Networks. Supervised learning. Multilayer Perceptron. Reinforcement learning. Learning Vector Quantization (LVQ). Unsupervised learning. Adaptive Resonance Theory (ART). Recurrent Neural Networks and other networks. Hybrid ANN Models. Neural Network Hardware. Applications of ANN.