This course is addressed to life scientists or bioinformaticians in academia or industry who are using the R statistical software and want to extend their knowledge.
This course is addressed to life scientists, bioinformaticians, and computational biologists who would like to learn more about general best practices in Machine Learning and get more out of their Machine Learning models: more precise hyper-parameters, more generalizable models, and more interpretable models.
This course is intended for life scientists who are already familiar with general concepts of NGS technologies and want to expand their knowledge and skills on variant analysis. Course material is available for free.
This course is addressed to life scientists or bioinformaticians familiar with “Next Generation Sequencing” who wish to acquire the necessary skills to analyse RNA-seq gene expression data. Course material is available for free.
This course is aimed at PhD students, postdoctoral and other researchers in the life sciences who are planning how to proceed with comparative genomics analyses to investigate biological or evolutionary questions of importance to their study system, particularly to leverage comparative genomics tools and resources to characterise the gene repertoires of their non-model species.
This course is addressed to computational biologists, bioinformaticians, researchers, scientists and trainers working in the life sciences who want to learn how to make their research and training FAIRer with reproducible notebooks and websites.
Want to learn about identifiers used in bioinformatics? This asynchronous e-learning course can be completed online, at the desired pace and in the absence of an instructor.
This workshop is aimed at both Ph.D. students and researchers within life sciences who are already using R for bioinformatics data analyses and who would like to start using R at a more advanced level.