You cannot really go practical in AI without academic rigor. You can do recipes of what's already been done using a TensorFlow book, but that's how far one can go. If one is serious in getting in AI today, a great way to do is read the following books, in order:
1. AI: A Modern Approach by Stuart Russell and Peter Norvig.
2. Deep Learning by Ian Goodfellow and Yoshua Bengio.
It is amazing how approachable both books are for beginners, but you will be diving a lot into academic stuff as you go along.
AIMA provides better introduction for wider area of subjects but PAIP is one of most elegant and timeless books for both programming and old school AI.
If you're shipping anything after 2010, you're not going to get within an order of magnitude within state of the art with that book (PAI), unfortunately.
There's basically no numerics in that book about anything that'll past muster at NIPS or ICML nowadays or would be shipped by one of the big corporate AI labs, I'm sorry to say.
PAIP is one of my favorite books ever, but taken as a book about the craft of programming, not about AI. AI has grown, and the broadness of AIMA matches the subject. (It does need another update, and I heard they're working on one.)
PAIP is also very, very high on my list as well. I'm very pro-lisp and still develop new projects in lisp (CL, Scheme) and promote it when/where I can. But the person who picks up PAIP wanting to learn AI might not necessarily want to worry about picking up lisp programming skills at the same time (nor is learning lisp strictly necessary). This is why AIMA is still the best option, IMO, because it employs a language agnostic approach.
For whatever reason, Sutton's was the first serious book I read in any area of AI. The balance between explaining the history, the concepts and the code is handled really well.
1. AI: A Modern Approach by Stuart Russell and Peter Norvig.
2. Deep Learning by Ian Goodfellow and Yoshua Bengio.
It is amazing how approachable both books are for beginners, but you will be diving a lot into academic stuff as you go along.