Public health is inherently a data-driven and data-intensive domain. The demand for timely generation and dissemination of public health information and findings has skyrocketed over the last few years. This course is intended to expose students to various visual representation techniques and tools and offers them the opportunity to learn how to successfully transform different data types and structures into compelling and interactive visual reports with the purpose of promoting informed decisions and engendering a clear and shared understanding.

In this course, students will learn about design principles and become familiar with exploratory and explanatory data visualization techniques to accurately distill complex datasets into coherent and informative insights for audiences with varying levels of data literacy. The class will also focus on critical thinking, problem-solving, and sound analysis practices to avoid cognitive biases when designing, thinking, analyzing, and making decisions based on data. The course materials, in-class datathons, and the course project are designed in the context of real-world application.