You can find all material online.
Trixi.jl is a numerical simulation framework for adaptive, high-order discretizations of conservation laws. It has a modular architecture that allows users to easily extend its functionality and was designed to be useful to experienced researchers and new users alike. In this two-part tutorial, we will first give a brief introduction to the Julia programming language. In the second part, we will demonstrate what you can do with Trixi.jl and how you can use it (and extend it) for your own research. You can follow the tutorials interactively using reproducible Jupyter notebooks provided in a companion repository. In addition, we will end with a hands-on session where you can try out Julia and Trixi.jl for yourself using these notebooks.
Note: The tutorial is intended for researchers who are already familiar with at least one other high-level language scientific programming language such as Python, C, C++, or Fortran.