Dive into Data – in collab with Bristol Uni and Engine Shed
Yesterday we welcomed University of Bristol students as well as school students to Engine Shed for the “Dive into Data” event which was part of University of Bristol’s Data Week.
Data Week, is an activity delivered by the Jean Golding Institute, a central hub for data science and data-intensive research at the University of Bristol. It’s a week-long series of workshops, talks and events in the field of data science and data-intensive research, including Python, open data, reproducible research, data analysis, live coding, deep learning and more.
Yesterday’s event was a collaboration between ADLIB, University of Bristol as well as Engine Shed. We invited four speakers to share and speak about their specific career journey, how they got into working in Data and the avenues they’ve taken within, followed by a Q&A, where students and pupils could ask questions. We heard from Daniel Keast, Analytics Enablement Manager at Bank of Ireland UK, Helen Tanner at Data Cubed Ltd, Brittany Harris, Co-Founder of Qflow as well as Rob Griffiths, Artificial Intelligence Technology Consultant and Ni Zhu, Technology Consultant, both at BJSS.
Afterwards, Geovation facilitated a hands-on practical workshop for the students to learn more about practically working with data. Geovation specifically crafted this workshop for the event, enabling users to discover the different components that make up an image and the tools used to analyse imagery. They were then able to try their own hand at deriving information from an image such as vegetation health. No prior knowledge was required and step by step instructions in python, a commonly used programming language for machine learning and computer vision, was provided.
The event tied in with our Data Recruitment team’s mission “Dive into Data” – all set to change the misconceptions revolving around what it takes to break into and build a long-term career in data.
Specifically, we feature the different backgrounds that can lead to a career in data. We share real-life examples of how to get into fields such as Digital Analytics, Data Science, Marketing Analytics, Data Engineering, Analysis and Visualisation, whilst showcasing real-life examples of the career paths that have unfolded.
We hope that this will make a real impact, to clear some myths and assumptions, in turn, building confidence across a wider audience that a career in data may be for them.