The “How I Teach” talk series is an invitation for anyone delivering professional development to life scientists and educators to share their curriculum, tips, technologies, and approaches. Email firstname.lastname@example.org to participate or complete a submission form to sign up to give a short talk and/or demo of the teaching skill you want to share. See full blog post for details.
Time and Date for Talks
LifeSciTrainers Community Calls May 2022
- Thursday May 19, 2022 16:00 UTC (Zoom registration)(see in your time zone)
- Friday May 20, 2022 01:00 UTC (Zoom registration)(see in your time zone)
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YouTube: Posted after the presentation
How I Teach Life Scientists…by Using Reproducible and Scalable Learning Environments
Geert van Geest, SIB Swiss Institute of Bioinformatics
Format: Short talk and demo
Take home messages
- Docker can be used to develop reproducible learning environments
- Containers can easily be hosted on a cloud computing service
- The combination of Docker + cloud computing service enables a teacher to create a highly scalable and flexible learning environment
While teaching topics in bioinformatics, setting up a computer learning environments can be challenging. Installing and using required software on the computers of the course participants can be tricky because there is usually a wide range of hardware specs, operating systems, versions, permissions, and settings. In addition, some processes that a teacher would like to run during the course might require a specific operating system or computational resources (e.g., high memory or a GPU). Here, I present an approach to host containers on a cloud service that enables the teacher to: (1) develop a reproducible teaching environment with docker, (2) scale calculations to a wide range of computational requirements on a cloud platform. We have applied this approach to several different courses, including the topics ‘single cell transcriptomics’, ‘variant analysis’ and ‘introduction to NGS’. All containers we have used so far are based on either Rstudio server, jupyterLab or VScode images and are therefore easily approachable by the participants through a web browser. The documentation and scripts to apply this method for teaching can be found at:
Tutorial Link: https://sib-swiss.github.io/AWS-docker/tutorial/