This is a special topics course responding to the coronavirus pandemic. We will employ big data analytics and machine learning (ML) techniques to process, identify key data features, infer, predict, integrate, classify, and extract unique insights from the COVID-19 Open Research Dataset. This open dataset brings together nearly 30,000 scientific articles about the virus known as SARS-CoV-2 as well as related viruses in the broader coronavirus group, and it contains the most extensive collection of machine readable coronavirus literature to date. Math189Z is a project-based online course using the materials selected from this dataset. Some of the project goals include helping the science community to understand data genetics, incubation, and symptoms or helping fill some gaps when scientists are pursuing knowledge around prevention, treatment and a vaccine. Additionally, another goal of this course is to become comfortable using GitHub as this tool is extremely prevalent in industry and academia when developing and deploying models. To that end, all code, reading summaries, and your final project will be hosted on GitHub. Background in calculus and/or linear algebra required. HMC students may add without a PERM. Off-campus students should submit a PERM, including a description of their math coursework completed or underway.