Most In-Demand Programming Languages AI Engineers Must Master in 2020

As Artificial Intelligence is becoming more and more dynamic today, its engineering and programming also need to be more versatile. And to serve this purpose, AI engineers performing in the contemporary market need to master their programming skills. Moreover, the very nature of the technology industry requires them to stay updated in the latest tech skills, latest advances taking place in the IT industry. AI engineers are in demand, job opportunities are plentiful, but where are the skilled AI experts?

AI comes up with amazing breakthroughs in the tech industry today. But to get there, they still require skilled AI professionals to take up the responsibility. As they embark on their journey in the AI career following are the topmost programming languages they need to learn.

Python

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. It's high-level built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms and can be freely distributed.

R

R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

Java

Java Programming is a general-purpose object-oriented programming language, designed for the development of software for consumer electronic devices such as TVs, VCRs, toasters, etc. Java is a platform-neutral language, which means it is not tied to any particular hardware or operating system. It guarantees users to 'write once, run anywhere'. Java language is supported by almost every operating system such as Sun Solaris, RedHat, Windows, etc. ava interpreter generates machine code that can be directly executed by the machine that is running the Java program.

Prolog

Prolog is a logic programming language. It has an important role in artificial intelligence. Unlike many other programming languages, Prolog is intended primarily as a declarative programming language. In prolog, logic is expressed as relations (called Facts and Rules). The core heart of prolog lies at the logic being applied. Formulation or Computation is carried out by running a query over these relations. Its key features include Unification (The basic idea is, can the given terms be made to represent the same structure), Backtracking (When a task fails, prolog traces backward and tries to satisfy the previous task), and Recursion (Recursion is the basis for any search in the program).

Lisp

LISP, an acronym for list processing, is a programming language that was designed for easy manipulation of data strings. Developed in 1959 by John McCarthy, it is a commonly used language for artificial intelligence (AI) programming. It is one of the oldest programming languages still in relatively wide use. In LISP, all computation is expressed as a function of at least one object. Objects can be other functions, data items (such as constants or variables), or data structures. LISP's ability to compute with symbolic expressions rather than numbers makes it convenient for AI applications.