This course presents introduction of ANN which is a representation of human brain. Two learning paradigms, namely supervised and unsupervised learning along with perceptron, backpropagation neural networks and self-organizing map algorithm are discussed. At last part, a technique for dimension reduction; Principal Component Analysis (PCA) is presented. All of the material will be explained using a slide and several hand-computation for each algorithm. This course can be completed in 2 months. At the end of this course, student will understand basic algorithm of ANN and implement it to solve real case problem.