Java vs. Python: Which Programming Language Is Best?

IT-technologies continue to increase and attract ambitious specialists seeking to build a successful career. The fast growth and constant changes about information technologies lead to the emergence of new and gradual extinction of obsolete programming languages. What skills should a programmer have and what areas to be interested in becoming successful in 2019?

If you are thinking about the direction in which to build your career, we offer an interesting fact: an increasing number of machine learning engineers are needed in the world. Neural networks and electronic brain have ceased to be fiction, and many companies are willing to pay generously for the development of algorithms capable of learning. According to TechRepublic:

By 2025, investment in the digital learning industry will exceed $ 235 billion.
By the end of 2019, the number of professionals working in this field has doubled compared with the previous period.
LinkedIn called the digital learning industry one of the rapidly growing jobs.

High motivation to get deeper into the issues of AI-powered and begin to acquire the necessary competencies for mastering a new profession.

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What is driving demand for computer-assisted learning engineers?

Some more statistics:

The number of open vacancies in the “developer of AI” direction from 2015 to 2019 has doubled.
The number of informal requests from employers over the past three years has increased in four times.
94% of vacancies marked “AI development” were intended for machine learning engineers.
41% of closed vacancies were re-published in less than 60 days.

These figures apply not only to North America but also to other actively developing regions.

The active development of the IT industry requires a constant influx of new personnel. To become truly successful in this area, accurate knowledge of code and programming skills is not enough. Companies are looking for people who can offer non-standard solutions to existing problems and thereby move technologies forward.

What programming language to learn?

Many specialists in the development of AI are attracted not so much by the opportunity to create something new and surprising, as well as a decent wage. According to Indeed, the average salary of machine learning engineers in the United States is about $ 135,000, which is only $ 5,000 less than the earnings of an analyst director or chief scientist. In the CIS, the prospects are also impressive.

To become not just a good, but also a genuinely sought-after programmer, HR managers advise to master additional skills and continuously monitor changes in the industry. However, you should start with the basics: learning the appropriate program language. According to the survey, the following words are most relevant for computer-assisted teaching engineers (in descending order from the most requested):

Python.
R.
JavaScript.
Java.
Scala.

Knowing one of these languages, you can build a successful career in programming, even if you do not want to deal with issues of artificial intelligence.

Java vs Python

Java

Java also belongs to one of the most popular and universal program languages. Its key advantage is its adaptability to line up with any platforms. Java is interesting not only for potential computerized learning engineers: backend Android developers, system engineers, actively use the language.

Recently, the hype around Java has diminished somewhat, due to the emergence of plenty of new languages. However, according to analysts, he will remain one of the most frequently used throughout the world for a long time. It is confirmed by the fact that it was Java specialists that were most often required in 2018 in the labor markets of England and Ireland.

Currently, a qualified Java developer can expect to pay $ 55,000.

Python

Python is a universal programming language that is used not only to create learning algorithms, but also to solve other problems – development of web applications, server software, and media tools. The peak of interest in Python arose in 2017 (coincides with the machine learning boom), and 2018 only strengthened this trend.

Such major market players as Google and NASA are interested in attracting engineers who know Python. Remarkably, it is suitable for beginners to learn. Among its features:

Having a clear and understandable structure.
Good readability.
Ability to connect extensive libraries.

The average income of an experienced Python developer in the US starts at $ 54,000.

Programming languages for non-programmers

Mastering programming languages in 2019 is a good idea not only for those who want to build a career as a developer. Knowledge of HTML and PHP opens up additional opportunities for all professionals whose activities are related to IT-technologies.

First of all, they are internet marketing specialists, SMM specialists, and SEO specialists. The effectiveness of their work depends mostly on the ability to use specific applications and services and to customize them for a particular project. Although the most convenient programs that do not require any additional settings from the user. For example, the Cluster SJ is included in the toolkit of many SEO specialists. The intuitive application allows you to upload critical requests in a convenient format, and within a few seconds breaks them up into semantic groups for further processing.

Conclusion

IT-technologies are so firmly established in the life of modern users that knowledge of programming languages will be a plus for specialists in any field. The most promising for studying in 2019 are languages that allow you to create self-learning algorithms. Python, Scala, R. Java, and JavaScript are more versatile – they are more often used than others in web development are.

If you are starting to learn to programmer, it is best to start with languages with a simple and understandable syntax. These include HTML, Python, PHP, and Ruby. The ability to create a simple code, set up a browser, run an application for a smartphone is essential not only for web developers but also for all professionals whose work is related to the IT-sphere.