Dear colleagues,
Transmitting Science is offering the course "Introduction to Bayesian
Inference in Practice".
Course webpage:
https://www.transmittingscience.com/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/
Instructors: Dr. Daniele Silvestro [1] (ETH Z?rich, Switzerland) and Dr.
Tobias Andermann [2] (University of Uppsala, Sweden)
Course overview:
On this course, we will outline the relevant concepts and basic theory
of Bayesian methods, but the focus of the course will be to learn how to
perform Bayesian inference in practice. We will demonstrate how to
implement the most common algorithms to estimate parameters based on
posterior probabilities, such as Markov Chain Monte Carlo samplers, and
how to build hierarchical models. We will also touch upon hypothesis
testing using Bayes factors and Bayesian variable selection.
The course will take a learn-by-doing approach, in which participants
will implement their own MCMCs using R or Python (templates for both
languages will be provided).
After completion of the course, the participants will have gained a
better understanding of how the main Bayesian methods implemented in
many programs used in biological research work. Participants will also
learn how to model at least basic problems using Bayesian statistics and
how to implement the necessary algorithms to solve them. The aim is
that, by the end of the course, each participant will have written their
own MCMC - from scratch!
For more information, please contact us at
courses at transmittingscience.com
Best wishes
Sole