Author of Learning Deep Learning here.
How to solve a practical problems requires much more well-rounded skills that mastering one machine learning algorithm or another (in fact, some problems don't require ML at all).
For a more general introduction to data science, see http://p.migdal.pl/2016/03/15/data-science-intro-for-math-phys-background.html. So yes: discussing things with clients, getting data, cleaning data, realising it is not enough, so asking client if they have more/different data, exploring it, seeing that some of it is rubbish, semi-manually cleaning it, creating a model, seeing it's ok, discovering that it fitted to some artefact, ... (and dozens, dozens of steps).
This link does not work for me (it redirects to my event list). I am not sure if it is because of privacy settings or anything else? In any case: what is its full name as it appears on FB?
I am interested, but not sure if I will be available on that date (40%?). Do you want to create a FB event? From my experience as an organizer of various stuff it works for seeing who is interested; of course it will attract more newbies and casual readers (I am in this category: up to date, my most serious interaction with LW is this post: http://stats.stackexchange.com/questions/28067/entropy-based-refutation-of-shalizis-bayesian-backward-arrow-of-time-paradox/28634#28634).