Analysis of big data and its dynamic visualization have become extraordinarily powerful tools in population health, equipping researchers and practitioners to drive understanding among the general population and link science to action. Beyond mere access to big data, public health professionals must have tools to coordinate and understand disparate data sources and to translate them for the benefit of non-academic stakeholders. The proposed course, “Analysis to Action: Harnessing Big Data for Action in Population Health,” will prepare public health students to approach big data with an active lens. A collaboration between several Mailman School departments, the course guides students to use big data for simulation and predictive purposes while developing skills in dynamic visualization to motivate action through a language shared by population health scientists, practitioners, advocates, and policymakers. This semester-long course will help future public health practitioners learn to exploit the power of big data, transmit complex knowledge to various audiences, and lead data-driven decision-making. Through the use of case study-based didactic and laboratory components, students will complete several scripting, data analysis, and visualization assignments. For their final project, students will be required to present analyses of intricate data sets to non-academic audiences orally and visually. With an enrollment of 50 from across all six departments, the course will be offered as an elective to second-year MPH students who have completed their core curriculum requirements. Instructors include an interdisciplinary group of faculty and administrators who will teach collaboratively in four segments: data analytics, simulation and prediction, visualization and communication and engagement. Currently, no similar course exists at Mailman, nor in other schools, programs, or departments of the University.