Firstly, make sure you have your weetabix, coffee or whatever gets you going in the morning. There are no slow starts, from the offset we jump straight into it and I think it’s important that you are focused and alert. I would encourage them to have an open mind and take this opportunity to be curious, listen carefully, and ask many questions where you don’t understand to clarify some of the more difficult learning concepts because it does get challenging. Where the going gets tough, do not struggle in silence. It will not help anyone, where you can ask your peers for help, use google, even ai tools can also be very useful for inserting code and asking what’s going on. But most importantly your tutors want to see you succeed and that means engaging with them also so don’t be afraid to be proactive and bring your queries to them.

My careers coach has been so helpful in helping me feel less overwhelmed and confused as to my approach with interviews. I also feel like I have been given a breadth of resources to help prepare for the practical side of interviews/assessment centers where my hard skills need to be on display.

The best part of this bootcamp was the opportunity to meet a cohort of people from different backgrounds and see the various ways in which they understood and applied data analytics which helped me refine my understanding and application of the skill within my own field. The diversity of the class uplifted me as it felt like although we were all coming from different places there was a sense of solidarity in our ambition to gain knowledge and understanding. I think this really helped me think more creatively and have a less rigid view on data analytics. I think the hard skills of learning R were aided by being surrounded with a supportive network and group of tutors. I think this helped me recognise that the learning process did not need to be linear but rather shoot off from bouncing around ideas with others in a symposium. I have made some connections that I really value and will reach out towards as my career progresses.

During the skills bootcamp there was a networking event scheduled into the week where I met Maike from Earthen Lamp. The mission within Earthen lamp is to provide data driven consultancy for cultural and heritage organisations such as museums. I instantly connected to this company and saw how I could fit myself in with the skills I had learnt from the bootcamp as well as the insights I previously had from my experience working within a museum. Although I have not been invited to an interview yet I am currently working on curating my CV and a cover letter for a data assistant role.

When I started the course I had the rather narrow perspective that data analytics was wholly numerical and inapplicable to someone such as myself who does not necessarily have a mathematical mind. My narrow insights into data analytics were broadened by the lectures that explored the theoretical definition and application of data analytics. Where I previously believed this was a concrete science made up of gruelling hours crunching numbers, I learnt it was infact a powerful tool which could expand the horizons of our understanding of problems and refine the routes taken to resolve them. These were revelations I found during the more theoretical lectures which took place helping the bootcamp class define and understand the various applications of data analysis. Tying this understanding with the practical application of data analytics whilst we learnt how to use R helped me persevere with the fast-paced learning. Knowing how powerful a tool this would be once I grew more confident in this skill is what motivated me to keep trying when the code would occasionally go wrong and opening myself up to trying again. Although I didn’t perfect my R knowledge within the two weeks of the course I believe I did show improvement and quickly adapted to at least having an understanding of where to start.

I chose to study the data analytics bootcamp course as the title drew me in with it’s association to creative industries. This was particularly enticing as I had previously seen data analytics as something inaccessible to an individual who has a more humanities based background. I wanted to see how data analytics could be integrated into the work I was already doing and perhaps how I could expand the horizons of understanding my particular field of work.