Artificial intelligence is officially here to stay and will only expand in the years ahead. Even now, the development process of AI is moving at lightning speed. You should focus on learning the best languages for AI development to be ahead of the curve.

You are viewing: 11 Best Languages for AI: How to Maximize Your Programming Know-How

Unfortunately, there are no right or wrong answers when it comes to selecting an AI programming language. So, what programming language will secure you steady work for the future?

Let’s look at the top options for a programming language that will allow you to enhance AI and machine learning.

Best Programming Languages for AI

There are tons of generative AI use cases for almost every industry, but especially for entrepreneurs. The trend of artificial intelligence rising to the surface isn’t likely to change any time soon. So, what can you do to be more prepared for the shift away from manual computation and content creation and onto AI?

While many people are fluent in multiple programming languages, everyone has to start somewhere. If you have limited time, you need to know which one to choose for functional programming to have steady work for the years ahead.

Here are our top choices for the best AI languages that you can start to implement today.

1. Python

Maybe you are ready to start a new career in web development or machine learning today. While there is a steep learning curve, many people will choose to start with Python. This is one of the easiest and fastest languages you can learn. It allows you to do many things with one convenient package.

Python is key to understanding AI and machine learning, which might surprise you because its creation predates both of these technologies. It was released back in 1991 by developer Guido van Rossum.

If you want to learn something that can assist with training machine learning models, Python is a clear first choice. It helps with rapid data analysis, but that isn’t all.

2. Java

Java is another powerful option when it comes to AI programming languages. Most notably, Java is a great option for those who are interested in the intersection between app development and AI tools. Of course, that’s not to say that it isn’t equally powerful for other types of web development.

Like Python, Java was introduced long before AI became the center of attention. Released in 1995, it is now recognized as one programming language that has a very large and active community. Its standard library is extensive and has many AI packages like the Deep Java Library and Java Machine Learning Libraries.

Many people will turn to Java for debugging purposes, making it a great general-purpose programming language.

3. Javascript

Looking for an AI programming language that won’t take you years to learn and master? Javascript may be the perfect solution for you. It is used for front-end and full-stack development, a cornerstone of the interactions most of us participate in daily online.

This programming language is key to AI development, particularly applications that are run in a browser. It helps with computation tasks and refines machine learning capabilities. Often, it is run with machine learning libraries, notably TensorFlow.js.

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You will find that there are tons of resources to teach Javascript, just as there are for Python. You will find online coding boot camps, lots of books at the local library, and even free classes from sites like the Code Academy.

4. Prolog

Prolog is a great option for anyone interested in growing artificial intelligence. It is very logic-based, which is ideal for AI development. Unlike some of the other programming languages, it is declarative, which allows programmers to set rules for the AI applications they are building and refining.

It is also great for natural language processing, simple systems, knowledge representation, and data structuring.

While Prolog can be one of the best programming languages to learn for the up-and-coming AI trends, it may not be the obvious first choice. This language still isn’t completely widespread, and you will find only a very small community of programmers for Prolog.

5. Lisp

Surprisingly, Lisp has been around a lot longer than Python and Java but is not as well-known as some of these other languages. It is the second oldest programming language. Originating in the 60s, Lisp is becoming one of the most sought-after skills for AI development due to its natural language processing.

However, that isn’t the only reason people are drawn to it.

Lisp was originally used for practical mathematical notation. Now, it is more focused on solving the core issues presented by those looking to expand AI programming.

One of the key reasons people still use this older programming language is because it lends itself to faster iterations and prototyping as people build more AI and machine learning models. This flexible language is great for creating the foundation of AI applications but is hard to learn.

6. Julia

Julia is one of the newer AI programming languages, but that doesn’t mean you should write it off yet. Because it features relatively simple syntax, it doesn’t have a sharp learning curve that makes it totally inaccessible to a complete beginner.

While not widespread yet, it could put your skills in high demand for someone interested in using Julia. Learning a lesser-known language right now could pay huge dividends if it increases in popularity and use in the decade to come.

Like Lisp, Julia is primarily used for rapid prototyping, which will prove to be significant in years to come with AI programming. Distributed computing is at the core of Julia’s programming language. It may never be the dominant language when it comes to AI, but it certainly serves an important function.

7. Haskell

If you work in data analysis in an academic setting, you may already be familiar with Haskell. Before we dive in, you should know that this is one of the hardest AI programming languages you could learn. Most of the time, it is not used just in AI but in teaching and research applications, especially in the realm of defining algorithms.

Haskell might be right for you if you are thinking about complete code correctness in your algorithmic functions.

Keep in mind that Haskell has some great functions for data analysis that could unlock some of the key tenets of machine learning. Its language is both functional and readable, which can be a great asset to someone looking to learn as many AI programming languages as possible.

8. C++

C++ is a great tool for memory management and is often used in AI programming. This programming language is already widespread for game development and even robotics applications – and for good reason. It is well-documented, making it easy for someone who understands how it works to shorten their learning curve.

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Why utilize C++ as your AI programming language of choice? Beyond its memory management, it is also extremely fast. As artificial intelligence needs to process large subsets of data and iterate over and over again, C++ offers the robust solution that developers truly need.

It takes slow AI and machine learning and transforms it into something lightweight and speedier.

9. Scala

Maybe your goal with programming languages is to find one that has a large community available to help when you get stuck. Scala certainly has a large, thriving, and ever-growing community of people who believe that it could be the future of AI and machine learning.

That support does not necessarily mean this is the easiest to learn, though.

Scala is ideal for those interested in learning programming languages that can help with large sets of data analysis and computing. In addition to dealing with data sets, it also can be used to form algorithms that enhance machine learning and artificial intelligence.

One important thing to note here is that it incorporates well with Java in machine learning libraries like ApacheSpark.

10. R

R was developed to help primarily with statistical computing and data science. As a result, it may not be the most widely used language, but it certainly has its place in academia and data science. You will find plenty of packages that make this great for artificial intelligence development.

It should be noted here that R tends to be very complex to learn and has minimal resources out there to help you. Unlike other well-documented languages and large communities of people you can turn to for help if you get stuck, R lacks these features.

It also tends to be a little slower, which may not be ideal if you are interested in rapid iterations and prototyping.

Like Scala, it works with many of the most popular programming languages to help you build plenty of powerful machine-learning applications.

11. Go

Interested in what Google has put forward when it comes to the artificial intelligence scene? Go was their brainchild and was designed to target some of the pitfalls of C++ without losing its capacity for memory management and the ability to quickly develop AI. Their open-source programming language remains supported by the tech giant.

It is fast and efficient while also presenting a great option for anyone wanting something scalable.

Even if you are completely new to AI and software engineering, you can get started quickly with Go. A complete beginner will find plenty of resources and can start to quickly put together programs and apps that utilize the rapid computation associated with Go.

Final Thoughts: Best Programming Language for AI and Machine Learning

The growing world of artificial intelligence and machine learning means that you need to be at the top of your game when it comes to learning a programming language. To maximize your ability to make web applications or mobile app development, you need some of these more modern languages to help.

Think about where you could be tomorrow if you invested some time today into learning one of these best programming languages for AI and software development!

If you are ready to make money coding, here is our complete guide to starting a new career. There are tons of great artificial intelligence certification courses you can take to give your skills the boost they need to score a well-paying and secure job.

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