Is a computer science degree overrated?

Computer Science, an overrated dream. Every kid who wants to pursue Bachelors of Technology, opts for Computer Science branch, even if the college is not up to the mark.

Today, everything is related to computer in some or the other way. Machines, which used to be operated manually, are being controlled by computers. Every service, government or private, which used to be provided in offices with living beings working in them, is now available on computer. Even the doctors are being taught operating on virtual dead bodies in their MBBS courses. But if everyone starts working “ON” the computer, then who is going to work on the “INSIDE” of the computer?

Computer is also a machine which does not only needs softwares being developed by the computer science students but also needs hardware which cannot be made without the help of those of the core branches which basically include electrical, electronics, mechanical and civil. 

Everyone can learn a programming language, work on a computer and become a computer expert but working with wires and other devices is not a piece of cake. 

Looking at the immense growth of computer science branch, every other kid is being attracted towards it but one needs to understand that in order to stay in the computer related market, updating oneself every second is a must because new advancements in this sector don’t take years to implement.

also read:Which fields of computer science are in most demand today?

 And one fine day, these advancements will come to a halt when there will be nothing new to be developed for a span of time and at that moment the graph will take a dip and everyone who thought taking up computer science would be beneficial, would be left to dry out. 

The core branches would again come back to where they were, interdependent on each other yet not completely dependent on a single machine called computer.

Consider the two words computer and science. The first’s gifts to the world are huge and range from the lifesaving ubiquity of electronic medical records to the opportunity to get in a virtual bar fight at any time of the day on Twitter. The second word, science, represents an intellectual movement that’s delivered great advances like the polio vaccine, a few trips to the moon and too many others to list. So why does combining the two words into computer science come up so short, especially when we’re looking to staff up our programming teams?

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It’s not that the field hasn’t delivered. There are petabytes of LaTeX files out there filled with brilliant ideas like new programming languages, clever search algorithms, machine vision algorithms and a gazillion notions in between. Many of these are wonderful.

The problem is that few of us really need much of any of it. One friend confessed that he’s watched a development team flourish by passing over CS graduates and hiring only physicists, accountants or some other kind of math-savvy person. 

These new employees are more practical and focused on getting the machines to deliver, which is pretty much what almost all businesses want to do.

Theory distracts and confuses

Many computer scientists are mathematicians at heart and the theorem-obsessed mindset permeates the discipline. One theoretician said that all mathematical proofs are really just programs and vice versa, at least in his mind. He’s not really interested in delivering code that does the work as much as proving his code is correct. Okay.

It’s rare for a CS major to graduate without getting a healthy dose of NP-completeness and Turing machines, two beautiful areas of theory that would be enjoyable if they didn’t end up creating bad instincts. 

One biologist asked to solve a problem in DNA sequence matching and they came back to him with the claim that it was NP-complete, a class of problems that can take a very long time to solve. 

He didn’t care. He needed to solve it anyway. And it turns out that most NP-complete problems are pretty easy to solve most of the time. There are just a few pathological instances that gum up our algorithms. 

But theoreticians are obsessed with the thin set that confound the simple algorithms, despite being rarely observed in everyday life.

Many CS professors are mathematicians, not programmers

One of the dirty secrets about most computer science departments is that most of the professors can’t program computers. Their real job is giving lectures and wrangling grants. 

They understand spreadsheets and grant proposals, not actually doing the research. This is why god gave them grad students. The last time many of them actually programmed a computer was when they themselves were in graduate school. Since then, bit rot and cobwebs have set in and the compilers on their machines probably won’t start.

Many required subjects are rarely used

Data structures are often the main topic for the second course students take in computer science. It’s too bad few of us use many data structures any more. We either plop things in object hash tables or push them into a database that does the thinking for us.

 It’s still quite useful for everyone to think a bit about the algorithmic complexity, but very few need to worry about B-trees or even linked lists. Not only that, but many of us have realized that we’re better off trusting a standard library than fiddling around with data structures ourselves. It’s too easy to make mistakes. Many organizations explicitly forbid roll-your-own data structures with good reason.

There are any number of other examples of subjects in the classic curriculum that just aren’t that important anymore. Compilers are complex and essential, but the only people who write them are students who are forced to create toy versions in a semester-long course. Even Apple used stock open source tools when it create the compiler for Swift.

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