COVID-19 pandemic has tremendously affected our day-to-day life affecting world trade and movements. Wearing a protective face mask has become mandatory. In the near future, many public service providers will ask the customers to wear masks to avail of their services. Therefore, face mask detection has become an essential task to help global society. This paper presents a simplified approach to achieve this purpose using some basic deep Learning packages like TensorFlow, Keras, and OpenCV. The proposed methodology detects the face from the image/video stream correctly and then identifies if it has a mask on it or not. As a surveillance task performer, it can also detect a face along with a mask in motion. The method obtains accuracy up to 95.55% and 94.23% respectively on two different datasets. We explore optimized values of parameters using the Convolutional Neural Network model to detect the presence of masks correctly without causing over-fitting.