Course introduction
Day 1. Direct Solvers and Matrix Decompositions
Day 2. Sparse Matrices and Iterative Solvers
Day 3. Solving ODEs
- ODE Solvers - AM exercise
- ODE Solvers - PM exercise
Day 4. Non-linear Optimisation
Day 5. Applied Bayesian Inference
- Applied Bayesian Inference - AM exercise
- Applied Bayesian Inference - PM exercise
Day 6-8. Projects
- Project description

Built with from Grav and Hugo

> Applied Bayesian Inference

Applied Bayesian Inference

You can download the slides for the AM lecture here

You can download the slides for the PM lecture here