Time series forecasting has several applications and can provide valuable information. Recently I worked on a project forecasting ambulance demand for the emergency medical dispatch in Oslo. Using machine learning, statistical methods and a combination of the two, we explored how to forecast the demand as accurately as possible. The aim of this article is to give a general introduction to the process we used to create these models, which I believe can be relevant for many other applications as well.