Coding programming on a Macbook
Coding is a must-have skill for anyone building AI products. It enables you to bring your machine learning ideas to life. Learning to code is fun and empowering, but it also requires time and effort. The last thing you want to do is start learning a language only to realize weeks or months later that the job you want actually calls for a different language.
Simply put: Deciding which language to start with can be intimidating.
Not to worry! This article will explain the basics behind the most popular programming languages used in AI and help you decide which to learn first. For each language, we will describe its basic features, what it does well, where it falls short, and which sorts of jobs use it most.
A Basic Roadmap to Programming Languages for AI
The five most important programming languages in AI are Python, C++, R, MATLAB, and Java. Before we dive deep into each of them let’s explore which to learn first.
For most people, the first programming language to learn is Python. It’s easy to learn, extremely adaptable, and has numerous libraries specifically for machine learning. For those reasons and more, it is the de facto coding language in AI. What to learn next depends on your career goals.
After Python you should learn:
C++: If you want to work in robotics, self-driving cars, or hardware.
R: If you want to work in academia or the financial industry.
MATLAB: If you wind up working at a company that still uses MATLAB (You should convince that company to switch to Python).
Java: If you want to build scalable AI infrastructure.
One last bit of advice: Don’t try to learn two languages at once. Focus on getting good at Python first. After you have reached its limits, branch out depending on your career goals.
Read on for a more in depth look at Python and the other AI programming languages.
