Summer Institute of Biostatistics & Epidemiology Now Open
Register today for these short, intensive courses providing practical and tangible skills.
The 43rd Graduate Summer Institute of Epidemiology and Biostatistics will take place June 9 through June 27, 2025. The program offers short skills-based courses ranging in length 4 hours to 2-weeks, with online, hybrid, and in-person format options.
Our courses are open to learners from around the world, both BSPH degree seeking students and individuals looking to learn material outside of a formal degree program. Institute participants often include graduate students, clinicians, public health practitioners, physicians in training, and those considering a career in public health or wanting to increase their skills.
Popular biostatistics classes include Introduction to Data Management, Statistical Reasoning in Public Health I and II, the Data Analysis Workshop series, and AI Programming in Python for Public Health. Popular epidemiology classes include Epidemiologic Inference in Public Health I and Practical Skills for Conducting Epidemiologic Research.
“In addition to the helpful and relevant content, I appreciated all the strategies and tips for optimizing effective use of these programs.” -Student praise for Introduction to Data Management
New classes offered for the first time in 2025 include the following:
- Data Visualization prepares students to create clear, accurate, and impactful visualizations for audiences in both academia and industry.
- Artificial Intelligence for Improved Patient Outcomes equips you with the essential skills to both build and evaluate AI and predictive modeling tools in medicine, and publish your AI success stories in top medical journals.
- Using Generative Artificial Intelligence (AI) to Improve Public Health introduces students to core concepts in the utilization of generative artificial intelligence (AI) tools.
- Leveraging Electronic Health Records (EHR) Data: Opportunities and Challenges for Evidence Generation explores the practical uses of and methods for working with EHR data, designed for students interested in real world evidence generation.
- Applied Epidemiologic Analyses for Causal Inference provides a hands-on introduction to the estimation of causal effects using generalized (“g-“)methods.
- Propensity Score and Related Methods for Estimating Causal Effects provides practical guidance on the use of sample equating methods such as propensity scores to estimate causal effects in non-experimental settings.
- Practical Genomics provides hands on training in computational analysis of modern genomics datasets using R and Bioconductor.
“I loved the teaching style and practical, clear way of explaining things...Going over the calculations using R, Stata, etc. was the best part, since that's almost always how we will do it in real life.” -Student praise for Power and Sample Size for the Design of Epidemiological Studies I
A full list of the courses offered can be found online, as well as information on tuition and fees.
