What is the difference between back-propagation and feed-forward neural networks?

By googling and reading, I found that in feed-forward there is only forward direction, but in back-propagation, once we need to do a forward-propagation and then back-propagation. I referred to this link

Is any other difference other than the direction of flow? What about the weight calculation? The outcome?

Say I am implementing back-propagation, i.e. it contains forward and backward flow. So is back-propagation enough for showing feed-forward?