In this talk, we first introduce the existed learning strategies for the solution of Differential Equations using neural networks. To expand the applications, we investigate how to extend these strategies to the solution of Parameterized Differential Equations.Several aspects, such as network architecture, datasets generation, training techniques and numerical results, will be provided.