SHARP Bayesian Modeling for Environmental Health Workshop

Overview




The Bayesian Modeling for Environmental Health Workshop is a two-day intensive course of seminars and hands-on analytical sessions to provide an approachable and practical overview of concepts, techniques, and data analysis methods used in Bayesian modeling with applications in Environmental Health.

Official SHARP Bayesian Modeling for Environmental Health Workshop
website link.

Course GitHub link.

Unfiltred shareable feedback from 2023 edition


"Wonderful course reviewing Bayesian modeling from basic concept to cutting-edge."

"The workshop provided a helpful, programming-centric introduction to Bayesian Modeling in an environmental health context."

"This is an efficient, in-depth course with lecture/lab pairs on topics including Bayesian workflows, temporal models, spatial models, and and non-parametric models. The course gives hands-on practice with the tools used for these analyses, with a focus on NIMBLE, but opportunity to work with INLA and ensemble models."

"It was a very interesting and fascinating course! I would recommend everybody to take the course. The only tip I would give is that you familiarize yourself with Bayesian Statistics beforehand."

"I was highly satisfied with the overall workshop structure and content. Learning Bayesian modeling from the basics to its applications brought me a lot of joy."

"This course was a great overview of how Bayesian models can be used within the environmental health/ public health arenas. User friendly with very knowledgeable instructors that made me excited to incorporate Bayesian models into my research!"

"The Bayesian team was really nice and answered several of our questions and concerns."

"Really wonderful practical introduction! I feel like I am ready to test out some of these methods in my own work."

"The workshop was a meticulously prepared, and every detail was thoughtfully addressed. It was an inspiring experience to have the opportunity to learn from world-leading experts in the field."

Photos of previous 2023 edition




Photos below by April Renae.