A fatal viral disease that has killed thousands and infected millions around the world is the unique Corona virus disease 2019- COVID-19. The usefulness of artificial intelligence in the quick and accurate identification of COVID-19 from X-Ray pictures is demonstrated in this work. It is a difficult issue for both radiologists and medical academics to classify the viral COVID-19. In recent years, the classification of images using deep learning has grown in popularity. CNNs have demonstrated their mastery in extracting a vast array of machine-generated information. By utilising CNN for feature extraction and classifiers for classification on publically available datasets, the chest X-ray pictures are categorised. A Deep Neural Network with an ensemble structure called CoEnNet is trained with various hyperparameters, and its performance is compared. The proposed model must provide notable performance in terms of overall accuracy with 98% when compared to other machine learning and pretrained CNNs models

CNN, Ensemble learning, feature extraction, pre-trained network, transfer learning, covid19, Viral Pneumonia, Chest X–ray.