Is AI programming as fun and challenging as normal programming? Many people may have this question. OK,let’s see what did former Software Engineer at Apple say.
In order to be a leader in AI you need a deep understanding of the math behind it, which requires linear algebra, calculus, and differential equations.
For anyone majoring in Electrical engineering, or computer engineering the background should already be there (they have to take math, physics, and comp sci courses).
The reason the jobs are so in demand, is because most comp sci curriculums do not require extensive math and physics, so you run into a lot of computer scientists who can ace logic, but stumble when confronted with something like the chain rule (which is used in the backpropagation algorithm). Hence the field of software engineering is flooded with programmers for areas such as web design, but when you start getting into fields that are heavy in a combination of math, physics, and computer science such as optimization, machine learning, computational physics, or any type of aerospace engineering computing ie turbulence simulations. The pool of people gets much smaller.
I will say that pool is smaller in America. Most non-American stem students or professors I have met, grew up wth a very strong foundation in math, and physics, so even if their degree title was “Computer Science” they were well versed in multiple stem subjects to the point where they could work in many fields.
This is why I have a problem with the lack of educational diversity in American college curriculum, every student in engineering should be required to take math up to linear algebra, and calculus physics up to physics three, but that’s my opinion. Lol
So it’s def fun for those of us who love math, physics, and programming, and if you want to see if it’s challenging then take an optimization course, or a pattern recognition course, and then you will see the fun we have in class 😉 .
P.s however, if you want to get a job in tech, you have to be able to pass a general software engineering Interview. So I recommend a diverse skill set instead of focusing on one aspect. Become a full stack dev who can also utilize machine learning and you’ll be golden.