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Depends what that particular course is supposed to teach. Stats, maybe some sort of intro course, or a programming course intended for non-CS majors are all courses where it could make sense to abstract away setting up complex environments -- just like how, in the business world, companies (SAS, etc) make tons of money abstracting away complex environments so businesses can have their employees focus on what provides value in that context.

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The majority of the courses that utilize JupyterHub at the moment involve some kind of stats work. They use JupyterHub to ease people with little technical experience into using stats libraries and coding generally, with the aim of giving them a high-level knowledge of CS principles and techniques.

An exception would be the example of the deep learning project work. In this case JupyterHub was utilized as an easy way to deploy a centrally managed, cost effective environment for a large class to use GPU resources without the risk of running up huge AWS costs for each student.

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