These are the top AI programming languages

In fact, PwC predicts that AI alone will contribute $15.7 trillion to the global economy by 2030.

And since well-known companies like ChatGPT only make up a small part of the AI ​​ecosystem, the career opportunities in this field also seem endless. According to the World Economic Forum’s 2023 Future of Jobs report, the role of AI and machine learning specialist is predicted to be the fastest growing job in the world.

Beyond its namesake AI expert, the technology is increasingly being used throughout the world of text. In fact, according to his 2023 Developer Survey on Stack Overflow, 70% of professional developers use or plan to use his AI tools in their workflows.

So how does AI work and be created, especially for people outside the tech world? Programming is at the heart of it.

What are the top AI programming languages?

Overall, Python is the most relevant programming language when it comes to AI. One reason for this is Python’s dynamism and ease of use.

“Python dominates the industry, especially for generative AI projects, due to its simplicity, readability, and extensive library ecosystem,” said Ratinder Paul Singh Ahuja, CTO and Vice President, Pure Storage. I am.

Rakesh Anigundi, AMD’s Ryzen AI product lead, goes further and calls Python a “stakes” language. In short, it’s a baseline skill that everyone working in AI needs to know.

LinkedIn ranks Python as the second most in-demand engineering hard skill in the US, behind “engineering” itself.

“In particular, skills in the major programming languages ​​commonly used in AI development (Python, Java, and SQL) rank among the top five most sought-after technical skills in the United States.” writes LinkedIn’s Head of Data and AI. , Ya Shu.

How can I learn an AI programming language?

The programming language that is most relevant to the world of AI today may not be the most relevant tomorrow. And more importantly, they may be the most underutilized in your company.

In any case, having basic skills in a language like Python won’t help you in the long run. Enrolling in a Python bootcamp or taking a free online Python course is one of the many ways to learn the skills to succeed. Students may also be exposed to Python during undergraduate or graduate level coursework in data science or computer science.

Anigundi also said it is important for students to be able to know how to efficiently set up their programming work environment and what packages are required to work with a particular AI model. It also helps that he is an expert in mathematics such as statistics and regression.

“We’ve always experienced these technology trends, but the pace of some of these changes, at least in my lifetime, is mind-boggling to me,” he said. say. “But that doesn’t take away from some of the institutional knowledge that different educational institutions can give you.”

Singh says it’s worth considering specializing in a subfield that suits your personal interests, such as natural language processing, computer vision, or robotics. It is also important to prioritize ethics and understand what AI really means.

However, one could argue that soft skills are more important than technical abilities, as AI technology is changing rapidly. Some of the key skills identified by Singh Ahuja include:

• problem solving and critical thinking
• creativity and innovation
• effective communication
• adaptability and commitment
• ethical judgment

Above all, demonstrating a passion and desire to learn through real-world experience will help you differentiate yourself in a competitive field.

“If you’re at a very early stage in your career, choosing a project, doing a project that demonstrates value, sharing it, writing a block, that’s how you create impact,” Anigundi says.