September 10-12, 17-19, 2024 09:00-13:30
In this course, you will become familiar with tools and best practices for scientific software development. We don’t teach programming, but we teach the tools you need to do programming well and avoid common inefficiency traps. The tools we teach are practically a requirement for any scientist that has to do their own programming. The main focus of week one is on using Git for efficiently writing and maintaining research software. Week 2 is more focused on good practices for reproducibility in (data) science.
The full content of the Best Practices and Tools for Software Development workshop is available on the workshop’s page on the CodeRefinery website.
Bonus: what you learn in this course is appreciated and used A LOT outside Academia! One ECTS credit is available if you are a bachelor/master/doctoral student.
You can follow the course fully online, but if you like to learn to live with your peers, we will also host an in-person room to watch the streaming and do the exercises together (only for week 1).
Have a look at ENCCS lesson materials where you can find multiple lessons on GPU programming, data analysis and HPC optimisation.
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and its associated countries .