[Answer] What Are the Differences and Connections Between a Big Data Major and a Computer Science Major?

[Answer] What Are the Differences and Connections Between a Big Data Major and a Computer Science Major?

Given the current situation, computer science has become quite a broad major, much like mechanical engineering. At the undergraduate level, it may cover a wide range of content, including essential foundational education such as mathematics and physics, as well as structural knowledge related to computer hardware, software, networks, and so on. It may also include some software engineering and programming-related courses, such as data structures or databases.

Overall, undergraduate computer science education is more like foundational training in computer science, while software engineering, artificial intelligence, or data science (big data) are extensions built on top of that foundation. I am not sure whether there are universities that offer a data science major at the undergraduate level, but even if there are, from a responsible educational perspective, most of the foundational coursework should probably be the same as that of computer science.

The main difference would be that such programs might add some specialized courses related to data science, such as programming, data cleaning, and big data systems architecture. Without these foundations, there will ultimately be blind spots in one’s knowledge structure. For this very reason, offering software engineering as a standalone undergraduate major can, to a large extent, be seen as somewhat short-sighted and overly utilitarian. If universities go even further and offer big data or artificial intelligence as undergraduate majors, that would be even more short-sighted than software engineering.