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What is the difference between a Computer Scientist and a Computer Programmer? What is the difference in the actual work they do in industry?(not in academia) Can you provide some real world examples too?
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In short: You should choose Computer Science if you like math, logic, or if you want to get into a specialized field in CS such as artificial intelligence, machine learning, security or graphics.
In the simplest terms we can put it, computer science is studying what computers can do (usually taught at university or college) while coding is the practice of making computers do things (not requiring any actual formal education). One of the best parts about coding is the fact that it's virtually open to anyone.
Does computer science pay more than computer engineering? On average, computer scientists in the United States make more money than computer engineers . Many computer scientists have master's degrees, while a higher percentage of computer engineers have only bachelor's degrees.
Computer science is an academic field. It's a little like studying mathematics. It's studying and researching algorithms, data structures, and similar.
Computer Programmers write programs; the term tends to be used to describe people in industry, although of course computer scientists write programs too.
An archetypal computer scientist would be someone like Don Knuth. His work on algorithms is legendary.
An archetypal computer programmer might be Jeff Atwood. We're using his site right now.
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Nowadays, one can call himself/herself a computer programmer even if the only language they know is VBScript. Cynicism aside, I have frustrations with some of the industry terminology myself, e.g. computer programmer or software developer.
See Definition of a software engineer, Difference between programmers and engineers
The difference between scientists and engineers is pretty clear though. Both need to know computer science, but the main focus of scientists is expanding the scientific body of knowledge, whereas engineers are focused on applying this knowledge in real-world systems.
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