**Abstract**

The Corona virus pandemic is the most tragic virus outbreak in more than a century. Corona has globally already taken the lives of four million people, across all continents. The virus has the potential to become very catastrophic, if a significant part of the world population does not have any form of immunity against it. In this project, the aim is to make forecasts on the number of daily infections in the Netherlands. Seven different models were implemented to forecast the number of infected people in a three-month time period. The sequential CNN model outperformed all other models substantially. The capabilities of CNN models in time series forecasting can be very encouraging in conducting more research on time series data with convolutional neural networks.

**Keywords:** time series forecasting, data wrangling, convolutional neural network, machine learning, ARIMA, time series analysis, time series modeling, computational intelligence
