Sparse Grids and Artificial Neural Networks are 2 function approximation methods. This thesis studies the integration of these 2 methods. Specifically, a sparse grids layer is appended after ANN for general regression problems. Different model training methods will be discussed and we will also integrate it in convolutional neural networks.