Mooc Reproducible research: new self-paced session from 20 mars 2020!

Making your research reproducible means taking up the new challenge of science to improve its results!

The Mooc “Reproducible research: Methodological principles for a transparent science” proposes methodological principles for open and transparent science. The course deals in a practical way with topics such as note-taking, computational documentation, replicability of analyses.

The 3rd session of this Mooc, proposed by Inria Learning Lab, is open for one year from March, 20 2020. All content is available from the start, with an attestation issued every 3 months: you can follow the MOOC at your own pace and according to your needs! The estimated time to follow the course and do the exercises is 24 hours.

This MOOC is for all of you, PhD’ s, researchers, master students, teachers, engineers from all disciplines who want to learn about modern and reliable publishing environments and tools. Arnaud Legrand, computer science researcher (CNRS/LIG, Inria, UGA), Christophe Pouzat, neurophysiologist (CNRS/MAP5 Univ. Paris Descartes), Konrad Hinsen, Biophysicist (CNRS, Centre for Molecular Biophysics, Soleil) will show you some modern and reliable tools: 

  • Markdown for taking structured notes
  • Desktop search application (DocFetcher et ExifTool)
  • GitLab for version control and collaborative working
  • Computational notebooks (Jupyter, RStudio, and Org-Mode) for efficiently combining the computation, presentation, and analysis of data

Course details

This MOOC consists of four modules that combine videos and quizzes with exercises for getting hands-on experience with the tools and methods that are presented. We propose three paths, each of which uses a different notebook technology:

  • The first path uses Jupyter notebooks and the Python (or R) language. It requires no software installation on your computer.
  • The second path uses RStudio and the R language.
  • The third path uses the Org-Mode package of the Emacs editor and the languages Python and R.

We will introduce other challenges of reproducible research. At the end of this MOOC, you will have acquired good habits for preparing replicable documents and for sharing the results of your work in a transparent fashion.

This course is mostly bilingual French / English. The videos in this course are in French but are fully subtitled in English. The remaining course material is mostly available in English as well.

A lot of content have been added for this session:

  • new videos about git/Gitlab, aimed at beginners,
  • an historical overview of reproducible research,
  • overviews and testimonies of the issues of reproducibility and transparency in the humanities and social sciences.

To see the course description and register now or before June 4, 2019, go to FUN plateform.

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