Training Strands
There are a variety of ways to categorise computing training for researchers. For the purposes of this group, we divide according to the expected research impacts, which tends to mirror generality of demand.
Strand 1
Bulk Training
Training that many students and researchers want. This is not necessarily low level, but tends to be. Many or most inexperienced researchers would benefit.
Impact: underpins a lot, but does not contribute to research directly
Examples: basic python; introduction to queueing systems; version control
Strand 2
Specialised Training
Training in languages and techniques with broad applicability but more narrow demand. These tend to be learned for a specific project or need, and benefit from having a specialist to teach and hands-on feedback to learn.
Impact: enables specific research projects, improves quality or impact of research output
Examples: MPI; Cuda; Fortran; Rust
Strand 3
Dedicated Training
Training on a specific technique or package used by a research group or field. Only specific researchers would benefit from this training.
Impact: enables specific research projects, training contributes directly to carrying them out
Examples: an MD package; an ML tool; Stata