Welcome to the CERN@school "Get Coding!" course. Click on the lesson link below to open up the corresponding Jupyter Notebook in your browser. Alternatively, clone the repository (and/or fork it) to your local machine to go through everything interactively.
- This code dates from 2016. While every attempt has been made to ensure that it is usable, some work may be required to get it running on your own particular system. We recommend using a GridPP CernVM; please refer to this guide for further instructions. Unfortunately CERN@school cannot guarantee further support for this code. Please proceed at your own risk.
- This repository is now deprecated, and remains here for legacy purposes. For future work regarding CERN@school, please refer to the Institute for Research in Schools (IRIS) GitHub repository. Please also feel free to fork and modify this code as required for your own research.
The data used in the lesson is taken from the Crookes dataset, a sample set of measurements made at the Royal Institution of Great Britain during the BIG SCIENCE event of 18th June 2013.
That said, if you're feeling inspired, please feel free to fork this repository, alter the content, and add more lessons - this is only the beginning of what you can do with CERN@school!
See the accompanying LICENSE file for information relating to
the licensing of the software featured here.
The image of the experimental setup at the Royal Institution has been released under a CC BY 4.0; further information may be found on the FigShare here:
https://dx.doi.org/10.6084/m9.figshare.4588300.v1
First of all, a huge thanks to all of the contributors to this course - whether via this repository, email, or offline - your feedback is very much appreciated!
There are many coding courses available online for Python and, indeed, many other languages. This course is focussed on coding in the context of scientific research with CERN@school, and so mainly works with examples based on CERN@school data and analysis. However, material and feedback from the RAL Scientific Computing Department's Python Masterclass and Codecademy's Python course has been particularly useful - thanks!
CERN@school was supported by the UK Science and Technology Facilities Council (STFC) via grant numbers ST/J000256/1 and ST/N00101X/1, as well as a Special Award from the Royal Commission for the Exhibition of 1851.
- Setting up a GridPP CernVM;
- The Crookes dataset on FigShare;
- The Institute for Research in Schools (IRIS) homepage;
- The IRIS CERN@school website;
- The Official IRIS GitHub Organization.