Resources

Explore the available resources, some are free for the UNIL community, and some need to pay for business professionals.

  1. Swiss Geocomputing Centre resources
  2. Learning resources
  3. Computational resources for the UNIL community
  4. Open source programming languages
  5. Web services for developers

Swiss Geocomputing Centre resources

Assets (Logos & more)

Follow this link 🔗 (https://github.com/Unil-SGC/sgc-assets) to access and download the logo and other assets of the SGC.

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 machine learning applications.
  • Hands-on introduction to Multiple Point Statistics: a introduction to stochastic simulation using multiple point statistics, a modelling approach based on the use of training images with the aim of generating realistic heterogeneity characterizing natural processes.
  • EPFL Coursera: a free platform called Coursera where they share plenty of classes. You can learn many things on all the different fields you’re interested. These high level classes are given by Professors of EPFL and others.
  • Youtube: Youtube is a less formal platform where there’s a ton of very good resources, 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.

Computational resources for the UNIL community

  • Scientific Computing and Research Support Unit, DCSR: The Scientific Computing and Research Support Unit (Division calcul et soutien à la recherche, DCSR, in French) provide computation and storage resources to the UNIL community as well as transverse expertise to the various faculties of the University and its affiliated institutes. The expertise ranges from high performance computing (HPC) programming support to full stack development consulting missions.
  • HPC support to FGSE researchers: In particular, a team with expertise in High-Performance Computing (HPC) is providing free support to FGSE researchers in a wide range of topics, including parallelization and optimization of codes, benchmarking, algorithm development and implementation, and help with computing time applications to HPC centers such as the Swiss National Supercomputing Centre (CSCS). The team members are Flavio Calvo and Margot Sirdey. Both specialized in scientific computing, they will be happy to help you! Flavio and Margot can be directly reached by e-mail at research-computing-fgse@unil.ch or during the weekly drop-in session (Geopolis 4631, UNIL). Collaborations in mid/long-term projects are encouraged. Here are some examples of topics:
    • Adapting code to the high-performance computing infrastructure (parallelization, optimization)
    • Advise/help with designing and implementing numerical schemes/algorithmic
    • Assistance to the infrastructure of the DCSR: running on the cluster, running on virtual machines, data storage
    • Automatization of data post-processing pipelines
    • Refactoring of code in view of public sharing and/or social development

Open source programming languages

  • Python: Python is a programming language that lets you work more quickly and integrate your systems more effectively.
  • R: R is a free software environment for statistical computing and graphics.
  • Octave: Octave is a free version of MATLAB, it can be useful for students who used this language during their studies.
  • Julia: Julia was designed from the beginning for high performance.

As for more detailed differences, you can read more: R vs. Python vs. Julia

Web services for developers

  • Git: Git is a software that helps developers and data scientists to store and manage their codes and other text-based resources, as well as track and control changes and collaborate with others. Several web-based services host resources managed with Git and help to make accessible these resources. GitHub is the best-known website, others are Gitlab, Bitbucket, or Codeberg.
  • Jupyter: Jupyter is a Free software, open standards, and web services for interactive computing across all programming languages.
  • Google Colaboratory: Google Colaboratory,(Colab) is a hosted Jupyter notebook service that requires no setup to use, while providing access free of charge to computing resources including GPUs.