Early diagnosis and treatment of brain cancer depend on the detection and categorization of brain tumors. Deep learning algorithms have produced amazing results in medical imaging applications including tumor identification. Most of this field's research has concentrated on applying CNN algorithms like VGG16, DNN, and ANN to this problem. This work describes the identification and classification of brain tumors using the Python Imaging Library (PIL) and the VGG16 deep learning algorithm. A dataset of 7000 MRI pictures categorized by tumor type served as the foundation for the research. The main objective of this study was to develop a high-efficiency, high-accuracy model. We suggested utilizing the VGG16 architecture and preprocessing images with PIL to ensure consistent images for training on a sizable dataset of brain magnetic resonance imaging (MRI) images. A novel technique we have used in our work is one that can analyze a single image and predict the presence of a tumor from the results. The research's methods produced robust tumor detection across the dataset with 96, 9% accuracy, indicating the value of the method in helping medical professionals make informed decisions when diagnosing the presence of tumors.

COVID-19 is a contagious disease caused by a virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019. The disease quickly spread worldwide, resulting in the COVID-19 pandemic. The outburst of COVID-19 pandemic had tremendous effect on the whole world and analysis of the data can be meaningful in many ways to better understand the effect it had in our society. This paper aims in the direction of analysis of COVID-19 daily information based on country and continent level in terms of understanding the number of cases and deaths and their relationship, besides this is aims to better understand the vaccination number by country and effect of cases/death how they have affected these numbers. The solution was created on analysis of a dataset that contains daily information on each country, and using MySQL, SQL and PowerBi to generate the results for this work in way of query results which have been transformed to visuals using PowerBi for better understanding for further research work on this topic.