Why I’m learning to code and you should too

Written by Louisa Smith, Vacancy Coordinator at The Careers Service

Learning to code in general or teaching yourself a specific programming language can seem a really daunting and somewhat dull task to start. It took me a number of attempts to commit to learning and to stay motivated. I’ve put together a few tips and tricks to help you decide whether learning programming is for you, and if so, where to start!

1. Do your research

There are so many programming languages out there it can be difficult to make sense of what will suit you. Personally, I felt it was best for me to start learning R – a programming language used for statistical computing and graphics. Since I was studying for my Biology degree at the time, the most useful languages to start with were either R, MATLAB or Java for SPSS. 

However, the best language to start with is usually Python, because of its versatility. Python is a simple language with straightforward syntax to learn, so if you don’t know what you will use programming for then start there! There is a lot of documentation about each language already out there. Whatever you are planning to learn, there is a 99% chance someone has already written a function for it. Remember, 5 minutes of reading can save you several hours of trial and error.

2. Find a project

Programming can become a chore when you are learning for the sake of it. In my experience, if you don’t have a project to focus on then you are likely to find programming software clunky and repetitive. After attempting to teach myself R during first year with no real objective, I quickly became frustrated and impatient when I couldn’t understand something. However, soon after I found a dataset I liked the look of I was out of my slump! I started with some public datasets online (see kaggle and data.gov). When I began playing around with data points and started to understand how my code analysed them I was once again hooked. Having a specific project or dataset to work with also allows you to put your work into context – and in the end makes for satisfying results!

Of course this is all dependent on the type of programming language you use, and what you aim to achieve by the end. There are hundreds of examples and models online for what you can create in each language. You might want to start by making a very basic game, perhaps look up a similar project online and make that a goal. SQL on the other hand is a popular language to use when working with a large table of data. With my interests lying around biological data, I focused on the results of my research project that analysed the behaviour of deer.

3. Be flexible

There are so many resources out there for you to use. I found that a combination of online courses as well as YouTube tutorials gave me a pretty good selection of information (check out codecademy and DataCamp). It is really important with any programming language to practice regularly – like any language, little and often enables you to retain more information. I found that making notes as I learnt helped me create a cheat sheet of kinds that meant I could pick up where I left off without too much trouble.

As much as watching someone else code can be an easy way to skip through a tutorial, for the information to actually stick I found myself practicing repeatedly (no one expects you to become an expert in a week) As long as you can fit in a bit of programming here and there in between other work, it will become second nature.

And most importantly, don’t give up!