Training courses

Warning

We are currently adding new online courses. Please contact us if you would like to add a new course.

Materials for the training courses given by Biocomputing Hub and the CAN

• Unix and command line
• git basis
• R basis
• nextflow & nf-core
• single-cell analysis
• ImageJ
• “Introduction to deep learning” CAN training course based on Fidle training course

Materials for the training courses given to the ENS students

• L3 Statistiques
• M1 Machine learning

Other online Materials

Roadmap to follow when you don’t know where to start

2024 CNRS Actions nationales de formations (ANF)

• “Good practice to develop in R” (co-organized by RIS and DevLog networks): materials and sources
• “R for computing” (co-organized by Calcul and RIS networks): “R computing on GPU using RKeOps” session (materials and sources )
• “Data Science with R : tidyverse” (organized by RIS): materials

Bioinformatics

• SIB training
• SIB training collection
• Pasteur Hub courses
• Migale courses
• Mod BAM format

Statistics

• statlearning

• Bayesian statistics

• The Gaussian processes book

  • Visual introduction to Gaussian processes
  • Gaussian processes with Python
  • Guide to help you choose a kernel
  • Recomendation for Gaussian processes
  • Practical guide to Guaussian processes

Deep learning

• A list of several references (courses, books, articles) on the subject
• Fidle training course
• MLFlow
• List of small exercises in torch

FAIR

• FAIR training
• PLUME Guide
• IFB Guide

Git

• Advanced git
• Travo: Distributed GitLab ClassRoom

Docker

• 5 Docker Best Practices
• Docker build check
• How Container Filesystem Works

Rust

• Numerical Computing with Rust on CPU Git sources
• Rust WASM
• training material through progressive exercises and examples

Python

• futurecoder

Programming

• Le Centre de Compétences CC-FR
• Research Software Quality Toolkit (RSQKit)