The course notepad found here is the central entry point for links and detailed information about course content and structure.
The potential applications of ML and deeplearning methods to Nuclear Physics research are numerous, and include detector development, data analysis techniques and even physical modeling. These techniques will be essential to ensure the highest-quality and -impact scientific results from existing and future experimental works.
This introductory course, held virtually via Zoom, will equip students and young researchers from the Nuclear Physics community with the basic tools necessary to begin implementing ML methods, and will involve theoretical descriptions as well as practical examples of the relevant topics.
Registration is now CLOSED.
Participants should be familiar with Python. For those wanting to brush up ahead of the course, there are lots of online tutorials and exercises: www.python.org/about/gettingstarted/.
