#DataYou: Dr Kehinde Bagaagba

Dr Kehinde Babaagba is a Lecturer in the School of Computer Science at Edinburgh Napier University. She also develops new modules in machine learning for the BSc (Hons) Data Science course funded by the DDI Skills Gateway, as part of its Data Education in Universities activities. Here, she explains how her love of maths and problem-solving led her into a data career – and why data offers opportunities for everyone.

I’ve always loved numbers and solving maths problems – from a really young age. That attracted me to computer science, which was one of the options at the university where I wanted to study [Redeemer’s University in Nigeria] – so I went for it.

I did a Masters after my degree and decided to move into academia – first in Nigeria, then Scotland. Over the years, I have learned about many different programming languages and techniques and I have always had a real thirst to keep learning.

The first time I was introduced to data mining and data science, I was hooked! A specialised software called Weka, which we used to analyse large quantities of data, really piqued my interest.

We would have different large data sets and several algorithms (a process or set of rules to be followed in problem-solving). It was mind-blowing to change a few settings in the algorithms and see the results. We could infer patterns and trends in data and that really exited me.

I was also very interested in cybersecurity and malware (software designed to deliberately cause disruption to a computer or network). My PhD thesis was about applying data science and artificial intelligence (AI) techniques to malware analysis,

I’m intrigued more generally in how we can simulate intelligence in machines and apply machine learning, AI and data techniques to real-world problems.

Practical applications of machine learning and AI are important in my lecturing. I love teaching modules like the fundamentals of machine learning because I can relate that to how I have applied my own learning – and talk about real-world case studies.

My research now is about applying machine learning and artificial intelligence to cybersecurity problems. By using big data, algorithms and machine learning, we can predict how malware is evolving to attack an organisation’s information assets – and learn how to do something about it!

More generally, data is the future. Everything we do is increasingly data-driven, and more organisations are grasping the importance of data, and data analytics. By understanding and analysing vast and diverse datasets effectively, they know they can really improve their business processes..

For anybody thinking about whether or not data is the right career for them, I’d say ‘Just try it! Some people think when you talk about data, it’s going to be complex maths stuff. The truth is that you can actually begin a career in data at a level to suit you. Many people are using data but don’t know it, maybe just by putting information into a spreadsheet.

You can start off in a data analyst role, and go from there. You would be surprised how much free support is out there in terms of advice, tools and courses.

It’s all about you and what interests you. But just remember; in years to come, understanding the importance of data, how to store it and how to interpret it will be needed in some form in most jobs.

The pace of change means wherever you start your data journey, it’s unlikely to be boring! The intelligent use of data is central to our response to all the big problems which plague 21st century society – climate change, global health challenges, economic and social inequality, food security – and, of course, cyber crime.

This is a very important contemporary issue and an area where both the criminals and the security responses are ever-more sophisticated – so my knowledge has to stay current. I will ensure it does – because I want  my research to play a part in efforts to use data and artificial intelligence to  detect and defeat malicious online attacks. That really makes me feel I am doing something useful for society.