The book looks fine, if a little random in its selection of topics, and it's probably as good a start as any, but is neither necessary nor sufficient. Much of data science in 'the field' is hunting down, gather and cleaning data. Knowing the right 'black boxes' to chain together in the right order to get the result you want, and knowing how to present the results in an easy to understand way so that the people that have to make the decisions can make the decisions they have to make.

Knowing the theory is important, but most of the time what you actually need know is to quickly knock together a script that pulls in, cleans up and merges some dirty data from 3 different sources, select the right out of the box algorithm for the situation and presents the results in a clear and pedagogical way.