“When I was studying at university (BSc Computing and Mathematics at Cardiff University and MSc Computer Forensics) only a few years ago, the term ‘data science’ wasn’t used widely, however is more common today. Data science has been growing rapidly over the past few years, which can be shown from the increasing prevalence of open source repositories. These tools are being contributed to by a variety of people across all skill sets and levels, for instance statisticians, mathematical modellers and data scientists.
My day to day work involves a wide range of different things, from programming, providing technical support to projects across the lab, working with industry and other organisations, and attending or organising events such as hackathons.
A current project I am involved with is the Ministry of Defence Artificial Intelligence Hackathon which is taking place at the end of November in London. I am providing support to the organising of this event, and during the event I will be acting as a technical mentor, which means I can share my skills and experience with emerging data scientists.
Last year I attended an internally run course, called the Data Academy, which is an intensive course allowing staff from across the lab to use their work time to broaden their knowledge in aspects of data science they are not familiar with. It also aims to create an active and engaged data science community within Dstl. Last year was the pilot and this year the course has been developed based on initial feedback and progressions within the data science space.
During the Data Academy last year, I was able to learn both by working closely with my colleagues in the room during hands on exercises and also through presentations delivered by staff from across the organisation. This allowed me to learn directly from experienced individuals in their respective fields and also gave me the chance to share my skills.
The Data Academy isn’t about becoming a data science expert, but is more about providing an introduction to data science topics. For instance, letting people know what’s out there, when to use particular techniques and tools and also any particular key hints and tips.
Some of my highlights from the Data Academy included:
Learning R programming skills
The chance to use the unique Defence cloud environment (D-Cloud)
Gaining an understanding of the principles of data science
Getting an overview of the variety of tools available and be able to pick the right one for the job
Getting an understanding of different data science areas (e.g. text analytics and visualisation), so that I felt I had a good starting point in each
Being able to share my skill set (e.g. Python and Linux) with other individuals and learn from others in areas where I was unfamiliar (e.g. R).
I’m using what I learned at the Data Academy in my project work on a daily basis, and I’m continuing to work with people I met at the Data Academy.”