Having previously worked in software engineering, then trained in mathematics (stats & OR), and since worked in OR for ~3 years, I have a strong opinion on this.
If you want to work in OR then it is expected that you are familiar with the topics in the book including some theory behind LP, MIP, and so on. In practice, the real difficulty in tackling a real world problem is in framing the problem in such a way that those methods can even be used in the first place. This is a different skillset. Also recognizing when a problem is too complicated for these methods to be used and it is necessary to resort to metaheuristics and in some case custom heuristics.
Having attempted many of the methods in that book including LP, MILP, MDP, graph algorithms, SA, GA, Decision trees, Markov chains, some queuing models, OptQuest..... my conclusion is that the clean mathematical methods tend not to fit many real world problems, at least not the really complicated problems, which is what I have faced almost exclusively in my work.
Rather, the only things which "worked" (by worked I mean - actually solved the real, full problem, and were actually released to be used in practice... for real... in the actual real world) were heuristics, meta-heuristics, simulation based optimisation, and statistical analysis of simulation output. To the point now where I don't bother trying the nice clean mathematical models on any big problem because it's a waste of time.
The book, unfortunately, seems to talk about the nice mathematical models and theoretical side. It is necessary to be able to talk in that language to operate in the field. But don't be fooled - the success criteria for many projects in this domain is "I got a paper published in a good journal", which in my experience is negatively correlated with "I got it to solve the real, full problem and got people to actually use it".
For that reason no I don't think this book will introduce you to many practical techniques you can apply to real world problems. However, it will equip you with a useful language and set of ideas. And you will know what the options are for computing solutions if you know that it can be reasonable represented in vairous formed, like LP, MDP, parameteric black box function, etc.