Learn

Planning to learn more about ROOT? This is the right page!

We offer ROOT courses and exercises, in Python based on Jupyter Notebooks. For these courses, you don’t need to install ROOT on your machine. You can directly run all the examples and exercises on SWAN (if you have a CERN computing account), or otherwise using GitHub Codespaces or Binder.

Three levels are available:

• Beginners: ROOT Introductory Python Course, which can be accompanied by its the video version. This course covers the ROOT basics.
• Intermediate: ROOT Advanced Python Course, which can be accompanied by its the video version. This course is about RNTuple, UHI, RooFit, Pythonizations and some more advanced RDataFrame features
• Advanced: ROOT Advanced C++ Course. This course is fully in C++ and covers aspects such as using basic ROOT objects, dealing with RDataFrame using only compiled code, dataset schema with custom classes using ROOT dictionaries and writing it to TTree and RNTuple datasets, likelihood evaluation with RooFit, as well as parallelism and performance considerations.

Would you like to install ROOT on your local system? Have a look to the instructions.

Finally, if you wish to delve further into ROOT functionalities, check the following:

• The ROOT beginners’ guide (aka “Primer”)
• The Manual where more in depth information can be found
• The full API Documentation
• The Tutorials

Lastly, in case you have a problem or a question, don’t hesitate to use the ROOT Forum.