New Course - Intro to Bayesian Uncertainty Quantification

We’ve just launched our latest course, An Introduction to Bayesian Uncertainty Quantification.

Delivered by our Data Science Lead here at digiLab, Dr Mikkel Lykkegaard.

After completing the course, you will:

  • have a clear understanding of the foundational concepts of probability theory and bayesian inference.
  • understand the different components of bayesian inference, namely the prior, likelihood, marginal likelihood and posterior.
  • have developed methods for uncertainty quantification for solving problems in the real world.
  • be able to solve simple inverse uncertainty quantification problems using direct methods and markov chain monte carlo (MCMC).

Full course details here.