If you are a data developer, then you need to invest in learning the right programming languages. There are a ton of languages on the market, but some are more reliable than others. You will have a lot more job security if you invest in the right field. There has been much debate with regards to which is the most suitable programming language a developer should use. All current programming languages have their strengths and weaknesses whether they are compiled or interpreted. However, some languages are more popular than others due to the learning curve and availability of support. This article, therefore, discusses the top programming languages of 2019.
Python
Python is one of the most important languages for data science. There are several reasons they are correct. The popularity of python has been on the rise and is showing no signs of waning. You will encounter it all over web applications, network servers, desktop application, media tools, machine learning, and others. This programing language might prove useful for application programming interfaces APIs or in back-end servers especially in firms dealing with site reliability or security. Likewise, other popular web development frameworks such as a pyramid, Django and turbo gear are all python-based. Lastly, python is a beginner’s favorite language as it is arguably the easiest to learn while still being a high-level and easy to interpret language.
JavaScript
Not many data scientists specialize in JavaScript programming. However, it is still a good ancillary language to have, especially if you are working on web projects. Slightly more than half of the entire developer’s community uses JavaScript. It is a very crucial language especially for front-end development and is increasingly gaining popularity in back-end development. Game developers and IoT programmers are also catching on to JavaScript. This language allows the developer to create interactive websites and is a highly useful web tool alongside CSS and HTML. If you desire to venture into web development, it is imperative to learn JavaScript. However, you can also do other stuff with it due to its simple user interface.
Rust
In case you have never heard about this programming language, Rust is a new language primarily implemented at the system level and is on the verge of bringing a radical change to how we perceive programming. It is great for data scientists. Created by the Mozilla foundation, Rust is a low-level language created for the sake of writing critical code. Its intended use is to avoid buffer overflows, dangling pointers, and other memory errors. The learning curve of this language might be considered steep for beginners. The reason is that it emphasizes specific rules aimed at memory safety. Nevertheless, veteran developers love it, and most probably in the next few years, its demand might skyrocket.
Go
This is a minimal programing language similar to python. It was developed by Google who is also heavy users of python. It is no wonder that Go is highly simplistic while at the same time as efficient as C++. This language provides much better tools for creating concurrent programs. In an era whereby millions of core apps are being coded, Go addresses this demand quite impressively. What’s more, it has in-built concurrency support. The language also combines the best aspects of object-oriented and functional programming, in addition to featuring an important set of built-in development features. Major projects that have implemented Go include the likes of Ethereum Cryptozoic and the Kubernetes projects.
Swift
In case you are an aspiring iOS mobile developer, you should consider learning Swift as a career prospect. Released in 2014, swift is a relatively new programming language. Apple Inc. has since adopted it as its flagship programming language for use in native Mac-OS and iOS application. Native apps seem to outdo hybrid applications. Furthermore, Sprite-Kit makes it a lot easier to create 2D games. Swift has deemed an improvement concerning performance and usability in comparison to Objective-C. Moreover, while using swift, its editor called XCode examines your errors for you. For this reason, it is considered a statically typed language. This makes your errors easier to follow up and works a lot faster.
Kotlin
This language is the creation of JetBrains. It is completely inter-usable with Java without any limitations. Developers can use it in any software that uses java. These include Android apps, server-side development and a lot more. Android developers have been using this language for a while now, and it is considered the most popular. Back in 2017, Google declared Kotlin to be the official Android Development Language. It functions flawlessly with all current Java frameworks and libraries and performs almost at the same level.
C++
This is a very flexible and efficient programming language. Since its creation in 1985, it has always been on high demand due to its impressive reliability and performance. The two most popular projects based on C++ are Google Chrome and Microsoft Windows. Most portions of Amazon’s official website are also written in C++.
Choose the Right Programming Languages as a Data Scientist
That concludes the list of the seven best programming languages you should contemplate learning for data development projects in 2019. Here is a take-home point; coding is similar to writing in a different manner. There is not a mystic moment when one becomes a programmer. The action of programming turns you into a programmer, and the same way writing turns you into a writer. Whether you are a writer who offers custom writing, writes news briefs, or magazine articles, it all takes time. But, the best programmers and writers have one thing in common – they are in a continuous learning process.
Final Thoughts
It’s important to keep track of which coding languages offer which strengths to stay on the pulse of the industry. What is more, you can also visit Coding Alpha and Sitepoint websites for more insights regarding how to become a skilled programmer.