Honestly I only interviewed people for data science, not data analytics, so I can't say for sure. For data science, we were looking for 61B level coding knowledge and DS 100 level data analysis knowledge, but also knowledge of how machine learning algorithms work / how to use them (both theoretical and practical), and some knowledge of how to build web systems. I imagine you could get an analyst job with just the DS 100 stuff, but honestly I can't say for sure.
I would say CS 189 is probably more theory than we looked for. If you know how to implement most of the major algorithms from scratch, that should be enough. (Not as hard as it might sound, many are less than a page of code.)
In terms of practical stuff... at least when I was at Cal, there wasn't a good course on how to apply ML in practice. I haven't taken this class but it looks like it's probably more than you need.