At Code Division we help our learners build a portfolio of their work to showcase their skills and achievements.
Our learners learn through a combination of theory and hands-on practice - this blend of learning encourages creativity, the development of problem solving skills and collaboration when working in a team.
Computing Science has the 5th largest gender imbalance for Males/Females and the highest of any major subject.
This project intended to look at the traditional routes into tech; schools, colleges and universities and determine whether there are issues or obstacles to girls/women accessing these courses.
During the PDA, I was the project manager of my team for the project “Women in Tech” and I was able to use my project management skills. All together this gave me the necessary confidence and experience to pursue a career in data analysis.
I enjoyed making visualisations and reports to tell the story of what subjects’ women are studying at Scottish universities. I also enjoyed discussing ideas and collaborating with my teammates and mentors.
I was always scared of developing scripts for automation. It was generally the guys in my team who did it. Since completing the course I have already automated some of the project work using the skills I learnt.
=SUM(all)’s Eco-Equality project was built on the hypothesis that the effective promotion of cycling as a viable means of transport could reduce a city’s fossil fuel emissions by 2030, reaching targets set by many cities in the face of the current climate emergency.
Just Eat bikes
The map above shows that Just Eat bike stations are not located in areas affected by multiple deprivation, exacerbating existing transport inequalities linked to poverty and emphasising lack of access to green transport.
While doing this project, I implemented the data analysis skills that I learnt during the course. I enjoyed learning and using new tools like Miro, GitHub, Tableau. It was a great experience to work in a team and learn from each other.
I am confident that, as a result of completing the course, given a large data set I will now be able to clean and interrogate it (using tools in Python or Excel) to discover, write up and present interesting stories that might otherwise be missed.
I thoroughly enjoyed the collaboration with my fellow teammates, this took me away from my comfort zone as I am more used to working on solo projects. So this has been a real confidence booster.