The top programming languages to learn if you want to get into AI

It’s safe to say that the age of generative AI is well and truly upon us, rapidly changing the world of work as we know it. According to the World Economic Forum’s 2023 Future of Jobs Report, more than 75% of companies are looking to adopt technologies like AI in the next five years, so it’s no surprise that career opportunities in the space are exploding, especially for developers.

But which programming language is leading the way? Python is without a doubt the most buzzed-about language for AI development. However, a decent programmer can work with AI in nearly any programming language, and other popular options include Java, R, JavaScript—and of course, C++.

The real task is to look beyond the hype and headlines to figure out what language best suits your skill set and interests, leaving you well-positioned to meet the growing market demand. Read on to explore what language you should be looking at if you want to explore a career in AI.

Mastering AI with Python

While all AI-related skills have seen a huge jump in demand, Python in particular forges ahead, and, according to a 2022 report from Stanford University, sits at the top of the ten most in-demand specialised skills for careers in AI.

Why is Python so popular? It’s intuitive and easy to learn, allowing for fast, iterative work. It’s also already well integrated into the AI ecosystem, as many AI frameworks, libraries, and platforms have been developed in Python. It’s a favourite language among data scientists and engineers and is widely used in machine learning and robotics.

As a free, open-source programming language it’s also very accessible; you can learn or study it in a lot of detail and there is plenty of community support thanks to a plethora of tutorials, courses, resources, and forum posts.

Rapidly changing landscape

However, the AI landscape is a rapidly changing one, and many industry pros are emphasising that when it comes to jobs in the sector, soft skills like ethics and communication are going to be just as valuable as technical ones.

A recent study of 692 business leaders across Europe and the US showed that 78% of them believe that integrity is one of the most valuable skills when working with AI, and will become even more important.

A role like Lead Machine Learning Scientist at SAP Berlin, for example, calls for proficiency in Python and experience with machine learning frameworks, but also exceptional teamwork abilities, strong leadership, and strategic thinking skills as well as the ability to collaborate cross-functionally (interested in the role? You can apply here).

And though there is no doubting Python’s popularity within the AI space, on the ground most jobs will require that you have experience working with other languages as well.

This role for a Senior Machine Learning Engineer at Experian in London, for example, calls for advanced proficiency in Python but also experience with languages like Java, JavaScript, C++, Go, or C# as well as good cloud skills with AWS and Azure (head here for more info on the role).

Powering AI’s core infrastructure with C++

While Python is excellent for top-level tinkering, often what’s going on under the hood is being driven by C++. If Python allows you to build fast and fluidly, C++ has likely been used to make the blocks you’re building with.

Almost every AI framework has its core written in C++. In fact, if you look at popular open-source machine learning libraries like TensorFlow and PyTorch (created by Google and Meta respectively), you will see that C++ features prominently (the GitHub repository for TensorFlow, for example, shows that over 50% of the project is in C++).

So which should you use? It comes down to your own work style, skills, and preferences — are you someone who likes to ship features and try things out? When exploring careers in AI, you will likely gravitate towards Python.

Or do you prefer working on impressive low-level, high-performance tech? Then you won’t be short of options with C++, and there would be a place on most AI teams for C++ developers.

For example, the role of AI Frameworks Engineer at Intel (hybrid, working from Romania, Ireland, or Poland), calls for excellent C++ skills, a strong production software engineering background as well as experience with architecture and a proven record contributing to large-scale, multi-component software systems (find out more and apply here).

The good news is opportunities abound, no matter your programming background, for those with a growth mindset and the right combination of soft skills.

Are you looking to take the next step in your AI career? Then check out some of the roles available now on the House of Talent Job Board

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