The main objective of this master’s thesis is to introduce a mathematical model which enables computers to imitate human’s learning process. For this purpose, simple and multi-layer neural networks are defined as objects that can be trained and a few examples for their usage are provided. Also, Backpropagation algoritam, whose main idea is based on gradient descent method and which enables neural network to learn by changing their parametar, is explained. The algorithm was implemented on a single-layer neural network. Lastly, Elman’s network was introduced as the simplest example of reccurent neural networks and its learning is demonstrated.