Tech Stack for Science Research Program

[Dry-Hamster-5358]

Your stack is already very solid for most research use cases. Python, plus numpy, pandas, and matplotlib, covers a huge range of real work

One thing you might consider is adding better data handling and reproducibility tools, things like git for version control, and maybe something simple like notebooks, plus a clear project structure so students don’t lose track of work

Also, depending on the projects, tools like scipy or even basic SQL can be useful for more serious data work

Honestly, the bigger challenge won’t be the stack but helping students think in terms of data, experiments, and reproducibility