Code projected on the face of a woman to symbolize AI

The term artificial intelligence was coined in 1956 at Dartmouth College. In the following 15 years after that, AI thrived as computer power increased. But soon, we hit the limit, and stagnation set in.

Luckily, technology is progressing rapidly. We’re now living in a connected world of big data, Netflix algorithms, Siri, and Google Home. It seems that we aren’t slowing down either. 

Good on you for wanting to get into a field that’ll be in high demand in the future! 

But where to start, right? What programming language is the best for AI? 

AI consists of algorithms based on mathematical principles, and those work in all languages. That said, some languages are better for programming AI than others because they may be faster, have a great community, helpful libraries, and other benefits.

In the next 6 minutes, you’ll learn about the top 3 programming languages for AI and an additional five for more in-depth knowledge.

I’ll also talk about some awesome projects that have come to life thanks to AI.

A word of caution: it’s going to be heavy on the jargon. If you don’t understand something, scroll down to the FAQ to read the definition.

To make sure this article is the highest quality possible, I’ve run it by the CEO of QuantumSense before hitting the publish button. QuantumSense develops AI to help you label your data and search your text documents based on the meaning of your search, instead of just keywords.

1. Python

Python logo

Python is an interpreted, high-level, object-oriented programming language that you can use for almost any project.

Python is extremely popular in AI development and has a big community supporting it. That makes it the ideal starter language! 

Thanks to community support, you have a massive amount of libraries and frameworks for AI development at our disposal. Use what others already created, instead of coding it all from scratch.

Fun fact: The creator loved Monthy Python so much that he named the language after the comedy group.

Why You Should Learn Python:

  • You always have support from the vast community.
  • You have a ton of ready-made libraries at your disposal
  • The syntax is easy to understand.
  • Coding something in Python is faster than most other languages.

Where to Learn Python:

This Udemy course is made for people like you wanting to learn Python for AI. The course includes R as well.

2. R

R programming language logo

R is an object-oriented language created to explore, model, and visualize massive amounts of data. It’s all about statistics and data science.

R is a general language, like Python, but it features numerous packages in the field of ML. Learning R will help you take your project to the next level by being able to interpret and use large data sets.

Why You Should Learn R:

  • You can effectively work with big sets of data, which you need for powerful AI.

Where to Learn R:

With this Udemy course, you’ll learn R and Python for AI in one go. It’s the same as the one I’ve linked above.

3. C

C programming language logo

C is a low-level procedural, compiled language you can use for anything. It’s not an easy language, but it’s a popular and powerful one.

C can do some heavy lifting because it’s a low-level language. Search engines run on C code because they need to be crazy fast. So do games that require a lot of computing power. 

Remember how I was talking about libraries you can just load into your Python code? Most of them are written in C, too. You don’t have to make your own libraries to be successful as an AI developer. But if you want to, C is the way to go.

Why You Should Learn C:

  • It’s ideal for projects that need to be fast in execution.
  • If you don’t find an existing library to solve your problem, you can create one.
  • It works great with Python.

Where to Learn C

This Udemy course is great for beginners who want to start mastering C.

Other Languages to Learn for AI

As I said, you can use any language to create AI. Those three are just my personal favorites. If you know your way around all of them, you’ll be well off. 

But those languages may not be for you, so here are some alternatives:

SQL is a programming language to store and retrieve data from tables. When we move away from theory, SQL becomes an important language for AI developers.

Julia has a far smaller community and fewer libraries. Because of this, Julia is more challenging to get into than Python. But it’s growing rapidly and for a good reason. It’s faster than R and Python and specially laid out for big data analysis and machine learning.

Lisp was created by the father of AI, John McCarthy. That’s why many consider it to be the best language for AI. I don’t believe that holds because, in the 60 years that Lisp has been around, other languages caught up to and surpassed Lisp in the field of artificial intelligence. However, it’s still handy thanks to its prototyping capabilities and symbolic processing.

Prolog is like Lisp, a vintage language. It’s surpassed by many languages today but has some useful tools for AI programming like pattern matching, automatic backtracking, and tree-based data structure mechanism.

Matlab is a high performing programming platform made for engineers and scientists. Many of the methods you’ll use for your project ready-made in Matlab. It’s relatively easy to learn, but it lacks miles behind Python in terms of programming features. It’s also expensive.

AI in the Real World (Try It Out Now!)

AttnGAN lets you turn text into images. When the developers fed it with a specific data set like dog images, it worked great! But now it is on the internet and needs to interpret wider sets of data. When you try it out, you’ll see that it’s a bit overwhelmed. 

Here’s a taste. I’ve used the paragraph above to generate this image with AttnGAN:

Image created by AttnGan
Image created by AttnGan

Talk to Books by Google is for my fellow book enthusiasts out there. Ask the AI any question, and it’ll scrape through millions of books to give you the right quotes.

Screenshot of Talk to Books by Google
Me researching how to write better articles 😉

Google has a ton of other fun projects for you to check out.

This Person Does Not Exist is equally fascinating as it is disturbing. Every time you reload the page, you see a new human face. The twist is, none of these people exist, and they never have. The face you’re looking at is entirely generated by an algorithm.

Image generated by This Person Does Not Exist.
An AI generated face that doesn’t exist.

Wait until you see a picture that’s supposed to have two people in it. The AI can’t handle that and makes one face look like straight out of a horror flick.

Conclusion – What the Future Holds

Old languages like Lisp and Prolog are making a bit of comeback, but I don’t think they will prevail. More modern languages have surpassed them and continue to grow rapidly.

And then there is the newcomer Julia who may soon be the queen of the hill in the world of AI programming. MIT developed Julia in 2012 and has not stopped working on it since.

It’s far from perfect now, but it gets the attention and support needed to outgrow all the others. Although, that might take another decade or two.

For now, just focus on learning the basics. You are entering this field as it is still young and you can progress with it. 

You’ve discovered what AI coding language you can start with and where to study them. It’s time to get to work and have fun!


What Is AI?

AI is short for artificial intelligence. The term covers everything related to making smart machines that can creatively solve problems without human input.

What Is ML?

ML is short for machine learning. It’s a subset of artificial intelligence and refers to algorithms that can be trained and improve themselves without additional coding.

What Is DL?

DL is short for deep learning. It’s a subset of machine learning that learns almost as we humans do! Instead of getting fed with data, like in machine learning, a deep learning algorithm will try to reach the goal through trial and error.

What’s a Neural Network?

Neural networks mimic the human brain. It’s a collection of algorithms that can interpret vast amounts of data.

What’s a Library?

A library in programming is a collection of pre-made code. Instead of coding the same things again and again, programmers can simply integrate libraries.

What’s a Low-Level Programming Language?

Low-level means that the programming language is closer to machine language and farther away from human language. Code written in low-level languages doesn’t need to be translated into computer language and is, therefore, faster in execution than high-level languages.

What’s a High-Level Programming Language?

High-level means that the programming language is closer to human language than to machine language (zeros and ones). It’s easier to write in high-level languages because they come more naturally. Code written in high-level languages needs to be translated to machine language and is, therefore, slower in execution than low-level languages.

What Does Compiled Mean?

Compiled means that a code file written by a human gets run through a program, the compiler, and is then readable by a machine.

What Does Interpreted Mean?

Interpreted means that the code gets translated into machine language every time you run it.

What Does Object-Oriented Mean?

Object-oriented programming (OOP) makes use of, well, objects. Those objects are bits of code in different files that can be reused and integrated wherever you want them in your code. It’s opposed to procedural programming where a computer would just run through the code line by line.