This is exaclty how we operate at my company and I have found it to be an 
incredible time saver.  The alternative requires detective work to solve every 
problem for every user.  If everyone is using the same Vagrant box then solving 
the problems of one user can be applied to all of the other users.

I know python is a prime offender on this kind of configuration issues,  but 
this technique is wonderful for many different sorts of software packages…  In 
one go you can have a complete system up and running with potentially many 
different pieces of software properly configured and running…  The instructions 
typically go,  install virtual box, install vagrant, clone this repo,  type 
“vagrant up”… and you are running. 

—joshua

On Dec 6, 2013, at 10:36 AM, Owen Densmore <o...@backspaces.net> wrote:

> Just curious.  Has anyone knowledge of this course and/or the 
> school/instructors?
>    https://www.edx.org/course/utaustinx/utaustinx-ut-5-01x-linear-algebra-1162
> 
> One interesting thing in the FAQ was computer requirements:
> What software do I need for the course?
> We will utilize VirtualBox, Vagrant, and Git, which are available for free. 
> We have configured a virtual machine for download to ensure that all 
> participants have the same software and environment. With it, you will create 
> a small linear algebra package using Python 3 and iPython Notebooks. 
> Detailed, easy instructions will explain how to download, install, and use 
> the software. If you are registered for the course, you will receive an email 
> alerting you when these instructions become available. You will be able to 
> access them at least a week before the course begins. (Don't be intimidated 
> by the jargon. We'll get you through it.)
> 
> That, on the one hand, is extraordinarily sophisticated, on the other hand a 
> comment on just how hard it is to configure a desktop environment for class 
> material.
> 
> Imagine telling someone that you'll have to have a computer within a computer 
> configured correctly to run the Python packages you'll be using!
> 
> I was more impressed by Stanford's Machine Learning class that just said: 
> Install either MatLab or Octave.  All our code will work with that.
> 
>    -- Owen
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