Artificial intelligence (AI) is a branch of computer science that simulates the human brain and performs various challenging and complicated tasks. An artificial neural network (ANN) is a computational model that simulates the human brain. ANN is composed of multiple nodes that simulate the biological neurons. The ANN model is multi-layered and is composed of an input layer, a hidden layer and the output layer. The model learns from the experience or training data. In each learning session, the strength of the inter-nodal connection is changed. The ANN model mainly learns by supervised learning, unsupervised learning, reinforcement learning and transfer learning. The ANN model building is a multistep process and needs attention in each step. The current chapter discusses the various fundamental aspects of ANN.