You can expect these to be open-source, reusable, in a git repository, and with a community you can join and give contributions to:
Python for Scientific Computing, by Aalto Scientific Computing, UiO, UiT, KTH. Not a basic Python course, but taking your from basic programming to the tools needed for scientific computing.
Linux shell tutorial or the shorter Shell crash course. By Aalto Scientific Computing, level: intermediate, covers basics but focus on scripting.
Introduction to MPI: Gives an introduction to MPI using a Carpentries lesson template.
Introduction to MPI: Derived from the above and taught at the PDC Center for High Performance Computing at KTH, Stockholm.
Intermediate MPI: ENCCS course material that can be a good step after going through MPI introduction (above).
Existing Research Software Engineering Training Material by INTERSECT: This is the currently best commented overview of available lessons around research software engineering that we know of.
Intermediate Research Software Development in Python This is a great resource for somebody who wants to go beyond the introductory Carpentries lesson about Python.
Introduction to High-Performance Computing: Introduction to UNIX shell, file transfer, and how to submit and manage calculations on a cluster.
ENCCS instructor training: This ENCCS instructor training material is focused on helping competent practitioners and experts teach their knowledge to others. It also serves a kickstart to teaching ENCCS lessons.
Lecture recordings by High Performance Computing Center North (HPC2N)
Github without Commandline by RSE at Stellenbosch University, South Africa