Our academies are designed to remove the barriers women face when breaking into tech and to give our students the skills and support they need to start their career in tech.
Emily joined our full-time Women in Data Academy earlier this year and since graduation has secured a role as a Data Analyst, and shares how TechTalent Academy helped her turn her passion for tech into a career.
What were you doing before you started the Women in Data Academy?
Before I started the training, I had just left a position in teaching and was unemployed. I already had a degree in mathematics and had a bit of programming experience however no industry credentials and no experience of the technologies and tools used in industry.
Why did you decide to join?
When the Covid-19 pandemic struck, I felt that I could not continue in my previous position and wanted to change career to something more liberating professionally that would also enable me to work remotely. I had some familiarity with programming and quantitative methodologies and so was very keen to retrain.
What did you think of the training? How did it help you?
The training was very easy to pick up and very accommodating. As I was working from home, the short sessions didn’t get in the way of my other obligations. They were focused enough to provide me with the foundation necessary to complete the assignments and develop my skills, on a schedule that worked around my lifestyle, rather than forcing me to rearrange my day around the study sessions.
The Women in Data Academy introduced me to a much wider variety of technologies and techniques than I had previously been aware of and enabled me to approach job interviews and application letters with far more confidence. Instead of worrying about being asked questions about things I wasn’t aware of, it was empowering to see a mention of a technology or being asked a question about a given technology and thinking to myself “I know exactly what that is”.
What module did you enjoy the most?
I really enjoyed learning about Python and how to make use of machine learning libraries, particularly sklearn and Keras. Another module I enjoyed was Pandas.
Within a few weeks of learning about Pandas, I was given the tools and the space to start applying what I had learned in my own personal projects, one of which was gathering data from the internet about the number of Coronavirus cases and plotting my own graphs. I was asked about this project during my interview and I believe that being able to show off what I had done, including making reference to my brand new Github page, was part of what impressed my interviewers so much that they offered me the position before the interview had ended!
I am now assigned to two projects in my workplace that relate to Coronavirus, so the skills that I gained during the training have already been put into practice directly.
What are your plans for the future?
I’m currently working as a Data Analyst and as part of my role, I’m using data analysis tools to contribute to reports and develop new technologies for use in the public sector. My typical day involves working in Python to clean and prepare data, and training models to provide feedback to end-users. Currently my team are in the early stages of planning for the specific tasks, which involves a lot of exciting exploratory work, and once we have determined the deliverables required by the end users, we can begin to start creating the technologies (dashboards and database interfaces) as well as compiling reports to inform the end-users of what we have found.
My long-term aspirations are to continue working in Data Science. I have really enjoyed being able to challenge myself and use my abilities to contribute to meaningful projects. I feel empowered as an individual to explore and use my talents in ways that develop my own skills through creating and learning.
Do you have any tips/advice for people who want to learn to code?
My advice would be to not be daunted by how vast it all seems. There are hundreds of programming languages, libraries, software packages and technical terms which can seem overwhelming, but the thing to bear in mind is that you don’t need to be an expert in all or even most of it.
If you dislike a specific technology, then there is almost certainly something else out there that will be more appealing. If you find yourself getting put off by a particular coding language or software, leave it and move on to something else, you can always come back to it if you feel like giving it another go. Don’t get stuck feeling like you can’t get into coding because of one particular thing you can’t master. The fact that coding is such a huge field should be seen as a positive because it means that there’s definitely something out there for you!
Are you based in the West Midlands and committed to starting a career in tech? Our Women in Data offers a full-time and part-time accelerated pathway to a career in Data Science. Find out more and register your interest to join one of our 2021 cohorts.