Case Study

Lightening the load for computational biology courses using Nuvolos

The Challenge

At the Department of Computational Biology of the Université de Lausanne, Prof. Nicolas Salamin is responsible for teaching programming to the department’s students. This means getting them familiar with the fundamentals of Python in the same way and starting from the same point of departure, despite the substantial variety of hardware and operating systems used by the students. What’s more, the course is large, with well over a hundred students. This means coordinating with a host of teaching assistants, making sure that all the coursework is quickly distributed to them as well as to the students and that the access permissions are set up correctly in each case. Coursework preparation and editing for each occasion the class is taught further contributes to the complexity. Prof. Salamin needed a solution that could address all these challenges and simplify the work, saving valuable time and – no less importantly – requiring a minimum of cognitive burden to use again and again. Enter Nuvolos, an integral solution for researchers and data scientists to make their lives easier and save them wasted time.

The Solution

Nuvolos is an integral, end-to-end cloud-based platform to provide computational researchers with all the tools they need to do their work. Not only does it support research with a best-in-class suite of all the familiar applications for quantitative science, and enable reproducibility throughout the research process by making collaboration and version control an integral part of the platform, but it even addresses use cases such as Salamin’s by having native-built support for course teaching. Setting up course curricula and sharing them with TAs and students is a matter of a few clicks, and students and TAs can simply be added or removed as instances in a course project – as few or many as are needed at any time. Nuvolos naturally supports all the necessary access control to ensure that the course teacher, TAs and RAs and students all see and receive the correct files and instructions. Even grading coursework can be done within Nuvolos – the platform saves researchers time and effort every step of the way.

The Outcome

For Prof. Salamin, using Nuvolos has proven its value. Integrated SSO support allows the Computational Biology students to sign in using their university ID, meaning onboarding and integration of new students is no longer the cumbersome process university administration often makes it. All students can run the necessary Python applications in the browser regardless of their particular hardware or OS, guaranteeing they all start from the same baseline and avoiding configuration and compatibility concerns. Even tablets or mobile devices are fully supported, enabling the modern student to use whatever they are familiar with to do their work without making their preferences the course teacher’s problem. 

Since Nuvolos guarantees resources for every student, and never charges on a per-seat basis, the class sizes of Salamin’s programming course are no obstacle to performance or feasibility. Nor are the applications themselves a constraint on course design – Nuvolos supports all the familiar tools of the trade, from SPYDER to R to Jupyter Notebooks and many more. Sharing documents and materials across instances can be done lightning fast by Salamin or his TAs directly in the platform UI, and any subsequent file corrections are just as fast by simply pushing the file to students as an automatic override. In short, Nuvolos has saved Prof. Salamin many hours of work on his course teaching at the Department of Computational Biology in Lausanne – he is already recommending it to his colleagues!

Key Benefits

  • Easy and smooth onboarding and coordinating between students, TAs, and course teachers even on very large courses

  • Saves enormous amounts of time on configuring, maintaining, and troubleshooting applications for student use, guaranteeing all start from the same baseline

  • Wide array of supported tools for computational science in their latest, state-of-the-art configurations, enabling course teaching on virtually any quant topic