I'm CS faculty at a US university. In the COVID era, I've committed to improving the students' online learning experience as much as I can using SaaS products that I can apply towards instruction.<p>Right now, the coding in my assignments is in Jupyter notebooks and homework assignments. I don't like it because there is a lot of time and friction (especially in setting up environments) between learning the content and practicing it.<p>I like how code instruction sites like Datacamp and Plurasite have interactive coding environments in the browser that enable the student to practice a concept as soon as they learn it. I'd love to pay a SaaS company to give me the ability to set up these sort of practice sections and embed them on lecture pages on my teaching platform.<p>I want almost exactly the tool Datacamp released called Datacamp-Light (https://github.com/datacamp/datacamp-light) But that doesn't look like an actual service and they don't support the packages/libraries I need. Repl.it might be the answer, but does so much and I'm not sure it has my use case. OReilly's Katacoda looks about right, but I think its meant to be enterprise software.<p>Anybody have any advice?
You have mentioned pretty much all the tools I wanted to mention (Repl.it, Katacoda, etc).<p>Hesitant plug: We do have a platform, <a href="https://iko.ai" rel="nofollow">https://iko.ai</a>, we started for our own use to do ML projects for our clients, but I don't know if it's suitable for your case. It has real-time, no-setup, collaborative notebooks with most of the popular packages pre-installed (30GB+ images worth of libraries). They can also install additional libraries right on the notebook.<p>People can work together on the same notebook, see each other's cursors, changes, and selections. They can execute that collaborative notebook on their own environment.<p>We use that to train our models, but we also use that for our weekly calls: we write the agenda in the notebook, then be on a call and go over it point by point editing collaboratively, adding snippets of code for proof of concept or to reproduce a bug in the product. This way we have the meeting minutes, with the executable code, and the prototypes in the same place.<p>The platform does much more than that (training, tracking, scheduling notebooks, deploying models, + real time dashboards for model monitoring, etc...), but you don't need all that. We've onboarded students our colleague was supervising for their final year projects on ML.