- Jan 9: Gaussian processes - applications and computations (optimization of function) : Lecture notes
- Jan 16: Gaussian process regression and Gaussian Markov random fields : Lecture notes
- Jan 23: Latent Gaussian models, spatial Generalized linear mixed models (GLMMs) : Lecture notes
- Jan 30: Project GPs.
- Feb 6: Integrated nested laplace approximation - INLA (fast approximate Bayesian inference, examples of GLMMs) : Lecture notes
- Feb 13: Template model builder (frequentist inference), Lecture notes
- Feb 20: Project
- Feb 27: New Markov chain Monte Carlo (MCMC) methods : Lecture notes
- March 5: Hamiltonian Monte Carlo methods : Lecture notes
- March 12: Project
- March 19: Sequential Monte Carlo methods: particle filters, Ensemble Kalman filters. Lecture notes
- March 26: Sequential Monte Carlo methods: particle filters, Ensemble Kalman filters. Lecture notes
- April 2: Project.
- April 16: New clustering methods and dimension reduction techniques. Lecture notes
- April 23: New clustering methods and dimension reduction techniques Lecture notes
- April 30: Project.