Try to find a problem (maybe within computer vision) that you care about and where you have labelled data. Then maybe try to implement ( i.e. copy and paste) basic versions of standard architectures and start training. It probably doesn’t perform well to begin with so you start fiddling with regularization and losses and layers and features and it gets better. If you feel a rush, you get the energy to carry on, watch youtube tutorials, take coursera courses and maybe even read papers. You are on the path to develop the practical wisdom that drives research and applications these days. Its all about getting you hands dirty. All those fancy looking papers are not a result of theoretical thoughts and careful planing. Rather, they had some ideas and started coding. It looked promising but it didnt work, but then they fiddled and got some more ideas. And it improved - and at some point, they had something they could publish.