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In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared a dataset of open sourced research papers. This data-set isa resource of over 45,000 scholarly articles, including over 33,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses. This freely available dataset is provided to the global research community to apply recent advances in natural language processing and other AI techniques to generate new insights in support of the ongoing fight against this infectious disease. Thereis a growing urgency for these approaches because of the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep upand extract insight from this growing body work.The goal of this project is to use NLP and other machine learning algorithms learnedin thiscourse to develop atoolthat can text-mine this database of research articles to gain useful insights about COVID-19 and how we might beable to tackle the outbreak, contain the spreadand flatten the curve. The overarching insights that can be acquired from this dataset are numerous and which aspect of the problem you decide to tackle is up to you. For example you may choose to use this dataset to better understand the transmission, incubation and symptoms of COVID-19, look to gain insights around which therapeutics and vaccines may hold promise and warrant further investigation, or you may wish to investigate the risk factors that make COVID-19 particularly deadly in some patients.The underlying goal of this project is to gain insights from this dataset tobetter inform how our healthcare system, government, industries can tackle this growing problem.