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.