Distributing the COVID-19 vaccine is a logistical puzzle that teeters on a delicate structure of chemists, data scientists, freight drivers, healthcare professionals, distributors, state health departments, and policy makers. When even one of these pieces in the structure is imbalanced, the whole vaccine distribution tower could tumble. The U.S. Federal Drug Administration (FDA) has authorized two vaccinations based on data findings from extensive clinical trials and manufacturers, which have been deemed safe for distribution and use under Emergency Use Authorizations (EUA). However, supply limitations and other pressing challenges have compounded the logistical complexities and contributed to the slow rollout and incomplete shipment of doses. With a projected 600 million vaccination doses required in the U.S and demand currently outweighing supply, a vaccination effort of this scale comes with risks and challenges across end-to-end vaccine distribution management.

If you intend to take the certification, this will be a good starting point. If you don't, this will help you develop the basic know-how needed to succeed in a rapidly evolving Machine Learning ecosystem. This is not a certification study guide. This article's objective is to provide a simple explanation of complex ideas and give a broad view of the subject matter. The outline mimics the GCP Professional Machine Learning Engineer certification guide.