Is max_depth in scikit the equivalent of pruning in decision trees?
Is this equivalent of pruning a decision tree? 


Though they have similar goals (i.e. placing some restrictions to the model so that it doesn't grow very complex and overfit), max_depth isn't equivalent to pruning. The way pruning usually works is that go back through the tree and replace branches that do not help with leaf nodes.


  If not, how could I prune a decision tree using scikit?


You can't through scikit-learn (without altering the source code).
Quote taken from the Decision Tree documentation: Mechanisms such as pruning (not currently supported)

If you want to post-prune a tree you have to do it on your own:
You can read this excellent post detailing how to do so.