Tell us about your background.
I am from Gomoa Obuasi, in the Central Region of Ghana. Growing up, I loved computers, and would often be found at Internet cafés. My parents noticed my interest and worked with an uncle to get me my own device. I also loved to nurse people and had a small first-aid kit I used to tend to friends and family with minor injuries.
I wasn’t sure whether to pursue studies in technology or medicine but I soon discovered that Information Technology was the best choice for me. I was introduced to building software through programming in my third year when I joined a Django girls’ meetup and we built a blog with Django in three days. I immediately fell in love with programming. I loved the feeling of manipulating lines of code in the text/code editors (IDEs) and have it rendered in the front end in beautiful user interfaces.
I have a passion for design, data manipulation and software development. Competitions keep me on my toes, so I try to participate in any hackathon I hear of, joining forces with others to form a team. I also love to teach and joined the teaching unit of the children’s ministry of my church and I volunteer for any tech-related program when I can.
How did you get interested in data science?
Not long after discovering programming, I heard from colleagues about how data science was a rapidly growing field that was helping to solve a lot of issues worldwide. At the same time, I saw an advertisement on Twitter about a quarterly data science meetup organized by Developers in Vogue so I decided to attend and to find out for myself what the buzz was all about.
My discovery both scared me and drew me in. It scared me because such a disruptive innovation has already caused such changes in how things are done around the world and was now happening in my country. I wanted to learn as much as I could about this technology and help spread awareness.
Next I attended a PyLadies meetup, and met a lot of data science enthusiasts who have been a great help to me in my journey. We worked together and created a team to compete in the WiDS Datathon and they trained me to keep up with the technologies they used in building the models.
How did you learn about Women in Data Science (WiDS)?
I first heard about WiDS on Twitter as contributors to the organization of a data science meetup for women. And my most impactful interaction with WiDS was when I was invited to join the PyLadies Ghana Data Science team, to participate in the 2019 WiDS Datathon. I was inspired by my team (Aseda Owusua Addai-Deseh, Kwadwo Agyapon-Ntra, and Abigail Mesrenyame Dogbe who is the PyLadies Ghana Lead), the number of women competing and the keen interest the organizers showed in our progress.
I learned so much during the month-long competition. I was a complete novice when it came to usage of data science tools to solve a problem, but this competition introduced me to new tools such as Keras and Fast.ai that my team used to create our models. I learned to clean and pre-process my data, visualize it using Tableau and D3.js and make inferences from those visualizations. There were resources available to study and datasets to use in our studies and practice. This pushed me to go further in my quest, as there was a large community to always lend a hand.
How has WiDS made an impact on your life and/or work?
WiDS has set a path for me in my data science journey because I now have a solid foundation to understand the concepts of data science and its applications. I can pick up tools at random now and work with them because of what I have learned. I have gained a lot of confidence and love for data science and would like to pursue further studies to get a Master’s degree in data science.
What comes next for you? And what are your hopes for women in the data science in the future?
I am currently doing my National Service in Ghana in the digital transformation team of my company and looking forward to continuing with my studies right after my service. I would love to see more women gain interest in data science and work with it and join the movement to get more women into technology and data science, as it is the future.