Learning resources

Getting Started with Machine Learning – a list of resources to help environmental scientists get started with machine learning. It included tutorials with codes, literature reviews, textbooks (often including code), and datasets that are already pre-processed for ML applications.

Hands-on introduction to Multiple Point Statistics – introduction to stochastic simulation using MPS, a modelling approach based on the use of training images with the aim of generating realistic heterogeneity characterizing natural processes.

Solving PDEs in parallel on GPUs with Julia – ETH’s course 101-0250-00L on solving partial differential equations (PDEs) in parallel on graphical processing units (GPUs) with the Julia programming language.

EPFL has a free plateform on Coursera where they share plenty of classes. You can learn many things on there, on all the different fields you’re interested in. These classes high level classes given by Prof. of EPFL and others.

Youtube is a less formal platform where there’s a ton of very good ressources, never forget to check and see if there are tutorials on there for your needs. Here are a few examples of Youtube channels with interesting content : Chrisitian Kaiser (Vice-director of the SGC) has a great channel for cartography (in french), the Bro Code for python tutorials, the AI guy for machine learning. There are many more channels to discover, these are only a few examples you can find.