Teaching Neuroimaging data analysis in the cloud using NeuroDesk

Introduction Researchers need a wide range of tools to analyse data and address their research questions. However, training researchers to use these tools is challenging. Many of these tools require Linux and are difficult to install due to complex dependencies. Additionally, neuroimaging analysis demands significant computational power and storage. This often requires extended pre-workshop setup instructions and forces workshops to use simplified datasets because of the limitations of participants' computers. Methods To overcome these challenges, we developed a flexible, cloud-based deployment of Neurodesk (www.neurodesk.org). This setup allows quick and efficient provisioning of a workshop on the cloud. We built on the Zero to JupyterHub project, which uses Kubernetes to deploy JupyterHub, and incorporated CVMFS to handle Neurodesk s software distribution. For smaller workshops, we created a K3s-based deployment that only requires a single virtual machine, avoiding the need for a full Kubernetes setup. Results This setup has been used in over 10 workshops and university courses, with overwhelmingly positive feedback from instructors. Many stated that the cloud setup made their courses more interactive and enabled the use of realistic data analysis examples. Cost efficiency was another major benefit, as resources could be scaled down when not in use, which was particularly important for GPU-intensive deep learning workshops. Conclusion The Neurodesk cloud-based platform has proven to be a valuable tool for teaching neuroimaging data analysis. Based on the success of these workshops, we are currently expanding the platform to support other scientific domains such as genomics, microscopy, and astronomy.