How deep should I go in learning data science, machine learning and computer science?
First of all, of course, we cannot lose focus of [petroleum] engineering. That’s what makes us “the Domain Experts” or SMEs. But this new industrial revolution based on data we are living in, requires a new set of lenses to understand, and discover things that were not so evident few years ago.
I am not saying you should turn in a professional programmer, and neither to be an amateur; it is about learning the bare minimum to be able to state a problem, describe the workflow, discuss with DS and ML experts, and work out a prototype before scaling it.
It is practically the same as we do in college with math. If I remember correctly, I took 8 math subjects, but that didn’t make a mathematician! Sure. I barely scratched the surface of math. To solve a problem in engineering we have to know the basics of math; the same with chemistry (6 courses); or physics (8 courses), which didn’t make of me a physicist either! I think the analogy would be applicable for statistics, data science and machine learning.
Besides, it would be silly to think that you learn everything that needs to be learned in 4-5 years of an engineering degree.
Keep sharpening the saw!