Hi everyone Instats and the American Statistical Association are offering a 2-day seminar, Applied Bayesian Modeling in Python <https://instats.org/seminar/applied-bayesian-modeling-in-python>, livestreaming September 18–19 and led by Dr Chris Fonnesbeck of PyMC Labs and Vanderbilt University Medical Center. Bayesian methods have become indispensable for researchers who need flexible models that naturally incorporate prior information and yield intuitive uncertainty estimates. This intensive workshop demystifies modern Bayesian inference through hands-on exercises in PyMC (v5.25+), taking you from foundational concepts—priors, likelihoods, and posteriors—to advanced topics like hierarchical modeling, MCMC diagnostics, and the full Bayesian workflow. Whether you’re a data scientist, applied statistician, or academic researcher, you’ll leave with practical experience translating research questions into PyMC code, fitting and validating models with ArviZ, and interpreting results for publication-ready insights. No previous PyMC or Bayesian background is required, though familiarity with basic statistics and Python tools such as NumPy and pandas will help you hit the ground running.
Sign up today <https://instats.org/seminar/applied-bayesian-modeling-in-python> to secure your spot, and feel free to share this opportunity with colleagues and students who might benefit! Best wishes Michael Zyphur Professor and Director Institute for Statistical and Data Science https://instats.org [[alternative HTML version deleted]] _______________________________________________ R-sig-Epi@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-epi
