If you are in the early stages of your career, have programming aptitude and only time to learn one computer language, which should it be? According to IBM’s Jean-Francois Puget, the answer insofar as data science and machine learning is concerned is clear: Python.
Critics associate Python programs with having slow run times. There are also other languages that can come in very handy. Java, C++/C#, for example, remain widely used languages that power many financial services activities. R, which is generally viewed as a purer language for hardcore researchers and statisticians, also has its enthusiasts. But if you want to focus on just one language, our developer friends favor Python as it’s widely used, easy to learn and is well suited to grow alongside the rise of Big Data.
But how about if you are deeper into your career? Is Python still the best language to learn?
If you find yourself in the heart of your non-programming career, we think it’s great for you to at least gain exposure to coding. You’ll probably never make a living at it, but having a basic understanding for how programming works can be highly useful in maintaining your relevance within financial services.
Again, we vote for Python and here’s why: some firms are beginning to make coding proficiency in Python a requirement for young recruits — and not just those destined for straight technology roles. As those juniors advance in their careers, they’ll likely bring their Python thinking with them. Sure, one day another language will come along that will make Python a thing of the past. But by that time, you’ll be retired on a beach in Hawaii. For the foreseeable future, Python’s ranks are likely to swell. So if you have at least a basic understanding of it, you’ll be well positioned to remain in the game.
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