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A global emergency has emerged in the form of the COVID-19 pandemic. If governments around the world are serious about lowering the impact of this worldwide epidemic, they must devote significant resources to studying this disease. This research looks into the disease's outbreak, trains datasets for the Indian region, and tests the number of cases over the following three weeks. Based on data acquired from the official portal of the Government of India throughout the crutial time period, we have utilised various machine learning algorithms, including a logistic regression model, to make predictions. When testing the models' efficacy, several regression models were used. In the three-week period of test data, the expected instances are anticipated to be approximately 175K--200K, which closely matches the actual figures. Both the government and medical professionals can use this information to inform their future plans. The goal of data science is to discover new patterns and relationships in large datasets by applying statistical and computational methods. Cleansing and preparing data, visualising data, statistical modelling, machine learning, and many other tasks are all part of it. Discovering trends and patterns in data, creating forecasts, and providing decision-making support are all possible with the use of these methods. Data types that they might encounter include both structured (like dates and numbers in a spreadsheet) and unstructured (like text, photos, or audio). Many different sectors make use of data science, including banking, medicine, retail, and many more.