I distinctly remember, while working at FOSSEE, when we were conducting hands on workshop in the labs of various institutes, we would factor in the significant time to reach early and setup all the dependencies on the lab computers. Back then we would use Enthought's binaries for Windows system to install everything. If we were lucky we would also find Linux machines in the lab and that would help a lot as we were really comfortable with installing the requirements using a CLI.
Recently we scheduled an AI/ML workshop for New Media Design students at NID Gandhinagar. While preparing for it I was looking for the resources. I knew about Project Jupyter and IPython notebooks but my understanding of them was very brief.
I found that JupyterHub is brilliant project in terms of setting up
the complete environment and sharing the resources with all the
students. Their offering of the-littlest-jupyterhub which is targeted
for 1-100 users hosted on single server is perfect. However it does
root privileges to segregate user environments. If
at NID campus we get access to a server, I will try and see if I can
set it up.
Otherwise, I also came across Colab from google, which has the complete package, all dependencies, libraries installed ready to be used and shared with the students. This also looks promising. I will try to put together some notebooks and exercises around the concepts we would be would be covering and see how both these solutions fare.
But compared to the manual setup we used to do back then, this looks like a cakewalk.