This course offers in-person and online training on data access, processing and modeling techniques commonly used in environmental health research. The goal is to prepare first year MPH students for conducting quantitative data analysis in the summer and during their second year. Topics include household/ambient air quality, environmental epidemiology, climate change, metabolomics, and epigenomics. Basic knowledge in each subject area will be provided via reading materials and pre-recorded lectures. Instructors will lead a discussion to the typical datasets in their actual research projects in an hour lecture, then work with the students on these datasets during a two-hour computer lab session. After this course, the students will be able to (1) perform data extraction and preprocessing, (2) conduct common data analysis, and (3) generate preliminary results. All coding will be taught in R. Standard class computer codes will be archived on Github.