Thinking about AI development? It’s an excellent career move. Not only are AI-related jobs growing in leaps and bounds, but many technical jobs now request AI knowledge as well.
First step? Learn one of the most popular programming languages. But which is the best programming language for AI?
There are many popular AI programming languages, including Python, Java, Julia, Haskell, and Lisp. A good AI programming language should be easy to learn, read, and deploy.
The language you learn will determine the following:
- How easy you can program AI applications.
- The tools, libraries, and frameworks you have available.
- The documentation and community you have for support.
Let’s look at the best language for AI, other popular AI coding languages, and how you can get started today.
What is the Best Programming Language for AI?
For most programmers, Python is the best programming language for AI. Other top contenders include Java, C++, and JavaScript — but Python is likely the best all-around option for AI development.
Let’s compare some of the major features of these four languages:
| Parameter | Python | Java | JavaScript | C++ |
| Code length | Short | Long | Moderate | Long |
| Performance | Slow | Fast | Slow | Fast |
| Typing | Dynamic | Static | Dynamic | Static |
| Difficulty | Easy | Moderate | Moderate | Difficult |
| AI Codebases | Plentiful | Some | Some | Some |
Why is Python the best programming language for artificial intelligence?
- Easy to learn. Python’s syntax is extremely flexible, and the language has many quality-of-life and ease-of-use features. Even non-programmers will find Python intuitive. This low barrier to entry is important because many data scientists and analysts working with AI don’t have a programming background.
- Well-integrated. Programmers don’t need to reinvent the wheel. Many AI frameworks, libraries, and platforms have already been developed in Python and are available as open-source projects.
- Well-documented. It’s even easier to learn Python because there are so many tutorials, projects, and bootcamps online. Less popular languages may not have as many examples available.
- Simple and easy to read. Code that’s easier to read is easier to develop. Python produces extremely readable, short code, especially compared to languages like Java.
- Platform-independent. Python can run on virtually any platform, from Windows to Unix. It doesn’t have to be compiled because it’s an interpreted language.
- Excellent visualization tools. Python has an extensive selection of data visualization libraries— essential to AI development. Data scientists can create attractive, human-readable charts with libraries like Matplotlib.
AI industry. Many employers are hiring Python AI developers. According to Payscale, the average salary for a Machine Learning Engineer with Python Skills was $112,178 as of 2022.
The most notable drawback of Python is its speed — Python is an interpreted language. But for AI and machine learning applications, rapid development is often more important than raw performance.
Other Popular Programming Languages for AI Programming
Of course, you can use other languages for AI. Technically, you can use any language for AI programming — some just make it easier than others. Let’s take a look at some of the other best languages for AI.
1. Java
- Pros: Java is a popular, general-purpose language with a large community of developers. It’s statically typed, meaning you can catch errors early and run programs faster.
- Cons: Java can be verbose and has a steep learning curve. It has very few quality-of-life features; programmers will need to do quite a lot manually.
2. Julia
- Pros: Julia was designed for high-performance numerical computing and has solid support for machine learning.
- Cons: Julia is a young language and consequently doesn’t have a lot of community support. Learning this language may be challenging.
3. Haskell
- Pros: Haskell is a functional programming language that emphasizes code correctness. It can be used for AI development, although it’s more commonly used in teaching and research.
- Cons: Haskell is challenging to learn. It can also be extremely confusing, as the language is very niche.
4. Lisp
- Pros: Lisp has been used for AI for many years. It’s known for its flexibility and symbolic, logic-oriented approach.
- Cons: Lisp can be difficult to read and write. It also has a small community of developers.
5. R
- Pros: R is a popular statistical programming language among data scientists. It integrates well with other languages and has many packages available. It is excellent for AI with robust data processing needs.
- Cons: R can be slow and has a steep learning curve. It is also not well-supported.
6. JavaScript
- Pros: JavaScript is a popular language for web development. Developers use JavaScript in machine learning libraries like TensorFlow.js.
- Cons: JavaScript is more complex and challenging to learn than Python. It’s robust and has so many options that it may confuse non-developers.
7. C++
- Pros: C++ is a fast, powerful language popular among game developers. It’s well-supposed and well-documented—and can be used for many different things. It’s also highly efficient.
- Cons: C++ can be difficult to learn and doesn’t have a lot of quality-of-life features—a lot of things have to be handled manually by the programmer.
8. Prolog
- Pros: Prolog is a declarative programming language that’s well-suited for AI development. It’s largely used for logic-based programming—the foundation of AI development.
- Cons: Prolog can be difficult to learn and has a small community of developers.
9. Scala
- Pros: Scala is a general-purpose language with many features suitable for AI development. It integrates well with Java and has a large community of developers.
- Cons: Scala can be complex and difficult to learn. Scala is primarily used for advanced development such as data processing and distributed computing.
Suppose you know any of the above coding languages for AI. In that case, it may be easier to develop AI applications in one of those languages instead of learning a new one. Ultimately, the best AI language for you is the one that is easiest for you to learn.
What Programming Languages Shouldn't You Use for AI?
Some languages aren't well-suited for AI development. These are generally niche languages or languages that are too low-level.
- PHP. PHP is a scripting language that's popular for web development. However, it's not flexible or robust enough for AI development.
- Ruby. Ruby is another scripting language that's popular for web development. But unlike Python, Ruby isn't great at rapid prototyping — it will take longer to create a working AI system.
- C. C is a popular low-level language among system administrators and embedded system developers. However, it's not well-suited for AI development because it doesn't have many high-level features.
- Fortran. Fortran is chiefly popular among scientists and engineers. However, it's hard to learn and doesn't provide many quality-of-life features, making development difficult.
A good programmer can write an AI in nearly any programming language. It's simply a matter of how complicated the process will be.
Conclusion
Python is the best programming language for AI. It's easy to learn and has a large community of developers. Java is also a good choice, but it's more challenging to learn. Other popular AI programming languages include Julia, Haskell, Lisp, R, JavaScript, C++, Prolog, and Scala.
If you’re just learning to program for AI now, there are many advantages to beginning with Python. You can hit the ground running and start developing immediately.
On the other hand, if you already know Java or C++, it’s entirely possible to create excellent AI applications in those languages — it will be just a little more complicated.
Ready to get started? A course is a great way to tone up your Python skills and propel your AI career.
Frequently Asked Questions
1. Which Language is Best for AI?
Python is the best language for AI. It is easy to learn, has a large community of developers, and has an extensive collection of frameworks, libraries, and codebases. However, Python has some criticisms—it can be slow, and its loose syntax may teach programmers bad habits.
2. Is C++ Good for AI?
You can use C++ for AI development, but it is not as well-suited as Python or Java. C++ is a complex language with a steep learning curve. However, C++ is a great all-around language and can be used effectively for AI development if it's what the programmer knows.
3. Can Python be Used for AI?
Yes, Python is one of the best AI languages. In fact, Python has become the "language of AI development" over the last decade—most AI systems are now developed in Python.
4. Which is Better for AI, Java, or Python?
In a vacuum, Python is better for AI than Java. It's easier to learn, write, and read. However, Java is a robust language that does provide better performance. If you already know Java, you may find it easier to program AI in Java than learn a new language.
5. Is Python or C++ Better for AI?
Python is better for AI than C++. C++ is difficult to use and has a very high barrier to entry. Few codebases and integrations are available for C++ because developers don’t use C++ as frequently as Python for AI development.
6. Why is Python Preferred for Artificial Intelligence Programming?
Python is preferred for AI programming because it is easy to learn and has a large community of developers. Quite a few AI platforms have been developed in Python—and it's easier for non-programmers and scientists to understand.
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