Software engineering is a discipline that’s ever-evolving. Cloud, migration projects, AI and automation and the no code/low code revolution are all trends that are changing the software development landscape.
Software engineering is set to generate 133 million jobs by the close of 2022, so it appears that despite the changes on the horizon, developers will be as high in demand as ever.
So if you’re a developer wondering what skills you need to master next, or where you ought to focus your learning, this article may be of help.
These are the top 5 coding languages of 2022.
Java.
Recent data cites that 47% of technology managers look for Java confident candidates. And when you think about the reach that Java has, it’s easy to see why. Java powers everything from mobile applications (including most Android apps) right through to massive operational systems.
Its breadth of use confirms Java’s vast versatility. It has a mass of extensive libraries and cross-platform support, which is probably why so many of the world’s developers favour Java as their preferred language.
Python is another Object Oriented Programming Language popular with developers (it features further down the list, so more on that in a minute). And while the two share developer esteem they have different functions. For web development, Java would be your go-to. However, if you were leaning toward data science and machine learning, Python would be your best option.
If you are already a Java developer and want to extend your skills, you’d do well to learn Scala or Kotlin. Both these languages run on Java Virtual Machine. Scala is great for big data projects, while Kotlin was named by Google as a first-class programming language for Android development.
Javascript.
Javascript is used by many websites as its client-side language. 43% of managers in the same survey are keen to boost their team’s Javascript expertise.
Although it has mass appeal, there are other factors that may explain Javascript’s enduring popularity. Thanks to open source libraries and runtime environments such as React and Node.js, Javascript is hugely versatile.
If you are new to programming, Javascript is a great place to start. Not only is it widely used, it’s beginner-friendly.
C/C++/C#
The C dynasty was developed back in the 1970s, and it’s still widely used today. 40% of technology managers cite it as being a skill that is missing from their dev teams.
C’s use spans operating systems, and databases and even extends to the embedded systems found in hardware ranging from microwave ovens to childproof locks.
C++ is the power behind major operating systems. Microsoft, Linux, and macOS, for example. It is also used for the engines of the best-known web browsers.
Experienced programmers would do well to learn C++. It is an impressive addition to a CV, prioritising power and versatility over ease of use.
Python.
We said we’d come to it, and here it is.
Many developers and managers alike love Python. Children learning code often begin here thanks to its ease of use. Python has a simple syntax and a shallow learning curve. This combination mean that writing in Python is as close to writing in English as coding gets!
It is also powerful; Instagram and Spotify were built using Python. Fintechs love it too thanks to its ability to handle complex mathematical tasks.
If you are a budding data scientist, Python should be your start point. Data scientists use Python to extract and analyse data using Python libraries like TensorFlow, NumPy, and SciPy.
If you are an aspiring data professional with goals to work in statistical analysis, data visualization, or predictive modelling, you should couple Python with R. R is another popular language choice among data miners and statisticians.
SQL.
SQL (Structured Query Language) is a contemporary of C. It also dats back to the 1970s, and like C is still widely used today. Programmers use it to query, modify, add, and delete the data in relational databases.
SQL knowledge is particularly important for data scientists and analysts who write SQL queries to extract information from a company database. Of course, this data means nothing on its own and must be analysed, which is where Python or R come in. Python and R have powerful data-wrangling abilities.
Scaling up your coding skills.
Once you’ve made your decision about which coding language to master next, the next stage is starting the learning.
Here are some ideas to get you started.
Peer learning.
An open source library such as GitHub or Bitbucket is a great place to start. Read the code until you have a good idea of how it works, and then see how different people approach problems. This will help you to start thinking more creatively.
Read books.
Working chapter by chapter through a book helps to get to grips with difficult concepts. Online tutorials do have their place, but it’s easy to get distracted. Books require you to concentrate with limited distractions.
Work on projects.
Using some of your free time to contribute to open-source projects is a brilliant way to enhance your skills. Work on one that interests you or even start your own project from scratch! These are also fantastic talking points at interview and really demonstrates your interest in coding to potential employers.
Network.
Being active in the coding community is a great way to improve your coding skills. Sites like Stack Overflow and Codecademy are networking gold mines, helping you to make valuable industry contacts.
Work toward a certification.
Industry certification will open doors for you. Not only will you fine-tune your coding skills in the process, but you’ll also achieve industry recognised accreditations to boost your CV. Hiring managers have confidence in your ability and certifications are evidence that you can learn to a standard.
Are you a developer looking for your next developer job? Head to the tech jobs pages of our website. We have masses of developer opportunities working with some truly special organisations.
Reach out today!
