Many of you are often confused between machine learning or software development which is a better career for you in 2021. When I started my career in coding, I had the same confusion as well. So, here in this article, I’m going to walk you through Machine Learning Vs software development to understand what the best career option is.
Machine Learning Vs Software Development
I’ve been in the industry for a little while now, so hopefully, I can contribute some useful information to compare machine learning Vs software development to understand what is best as a career option. In this article, I’ll make a comparison between machine learning and software development so that you can easily choose a better career.
Money is important and many people are drawn into coding precisely because of the money, and there is probably nothing wrong with that. So let’s take a look at the salary breakdown of machine learning experts versus software developers in the US and UK. So first, let’s look at the US market.
On average, software developers earn $ 92,000 per year. This can be compared to $ 114,000 for machine learning experts, again, on average in the UK the situation looks quite similar. This data comes from Glassdoor. It does not take into account the geographical distribution in each country.
So, for example, if you’re working as a software developer or machine learning expert in a region like Silicon Valley, you’re going to earn a lot more than what I just mentioned above. It’s just an average and the same for London in the case of the UK.
The point is, as you can see in both countries, machine learning experts earn slightly more than software developers. But what about the demand for machine learning vs software developers? To analyze this, let’s take a look at the number of vacancies cited by, Indeed.com.
So, according to the website, between 2015 and 2018, the number of job postings for machine learning experts increased by 344%. And the number of software developer positions increased by 207% during the same period. You can see remarkable growth in both areas. But again, the number of job postings for machine learning has grown a bit more compared to software developers.
So, when it comes to the financial side of Machine Learning Vs software development, it looks like machine learning will win out.
The second aspect that we will consider here is your predispositions. Now I believe this is the most important factor in the whole decision-making process. And what I mean by that is that machine learning and software development are completely different fields. They require completely different skills. And you have to have completely different mindsets to solve machine learning problems versus software development problems.
Now, you might be naturally more adept at machine learning, or maybe you are more naturally adept at software development. So let’s compare and see what machine learning is. Well, machine learning is a statistic, period. Statistics mean mathematics. If you’re not good at math, forget about machine learning. And I’m not saying you can’t learn it because you probably can if you put enough effort into it.
What I am saying is that you will find it extremely difficult. And what’s the point? Machine learning is therefore intended for someone who enjoys complex mathematical puzzles, thinking in an abstract and theoretical way. So what is software development? Well, software development is a type of engineering and that means putting things together to make them work. It is a much more practical area.
What is important is your creation. Hippity practice, it is not important that you know the math, because usually this is not involved in the process. So that’s a distinction between machine learning and software development. Another distinction is that in software development you get this instant system feedback so you do something, you called your solution and it works or it doesn’t.
You get this feedback and you know you did something right if you did something right. And that makes you happy. While in machine learning, there are so many arbitrary things that happen in machine learning. If you get very questionable results, you may not have cleaned your data properly. Or it might be that the data is inherently messy and it isn’t much you can do about it. Or it could be that you initialized your hyperparameters to the wrong values, or it could be that this algorithm isn’t the best fit for the data and it could be, you know, a series of things and that you just don’t know.
And you will never know for sure what it is. And because you don’t know if you’re doing something right or wrong, it doesn’t give you that instant satisfaction, that instant feedback. The number of technologies you need to know to do machine learning is quite limited, which is good or bad, depending on how you look at it. But basically, all you need to know is Pythonesque.
Well, your job is to find algorithms so all the math is more important. And then the idea is that you just have to put it in a code. Python is sufficient for this. One downside to software development is that you have to know a lot of programming languages, especially if you are a Full Stack developer, which means you have to know the backend and the front end.
So in this scenario, choosing between machine learning vs software development depends on whether you are a lot of complex math, then like to read or like to create things, build things, then software engineering is for you a draw.
Barriers to Entry:
The third consideration concerns barriers to entry. For machine learning, the barriers to entry are quite high. Very often in job advertisements, you will see that what is required is an advanced degree in mathematics, statistics, computer science or other quantitative degrees. Sometimes they even explicitly ask for a doctorate in these fields.
However, this is not always the case. However, it often happens that this degree is at least useful. It can be compared to software development. Sometimes job postings ask for a degree, but rarely is it a graduate degree like a master’s or doctorate. And even if you don’t have a license, often having a portfolio of projects you’ve coded is enough to prove that you know how to code.
So in this category between machine learning vs software development, I think software development takes precedence over machine learning.
Machine Learning Vs Software Development: The Future
So let’s talk about the forecast for the next 10 years, what is the right option between software development or machine learning. Surprisingly, machine learning is still on the rise given the insane amount of data we produce every day. 500 million tweets are sent, 4 petabytes of data are created on Facebook. 294 billion emails are sent. 4 terabytes of data are created on each connected car. Over a billion messages are sent on WhatsApp, five billion searches are done.
So we generate a lot of data and somebody will have to extract information for governments, for companies. And I also think that many machine learning experts in small businesses, in particular, will need to acquire the data engineering skills, because the data engineering skills will be extremely important. Software development is not going anywhere for the next 10 years as well.
However, this trend is that we will code less and less. It is happening now and it will certainly be even more important in the future. So basically software development is going to be about glueing things together, understanding the ecosystem, how different applications talk to each other.
So we have a tie between machine learning vs software development as a career option. Now to choose the right one for you, ask yourself these questions:
- Do you prefer math puzzles or building things?
- Do you have a specialized degree or can you afford one or not?
Because a degree can be a prerequisite for many machine learning jobs. It doesn’t have to be, but maybe. Answering these questions should help you decide between the two career options.
I hope you liked this article on how to choose a better career for yourself between Machine Learning vs software development. Feel free to ask your valuable questions in the comments section below.