The Data Science for All / Women - 2021 program ended on a high note on October 29th with a Grand Finale event to celebrate 250 Fellows’ graduation from the program. The event featured Fellow testimonials, a virtual showcase of the winning capstone projects and keynote addresses from inspiring speakers sharing words of wisdom with the graduating class.
DS4A / Women 2021 in Review
We kicked off the Grand Finale with Fellow testimonials, where the Fellows reflected on their experiences, shared lessons learned, and recalled some of their favorite parts of the DS4A / Women experience.
Capstone Projects Finalist Showcase
The capstone projects are a core part of the program, helping Fellows apply data concepts to real world business problems.
Teams were formed of Executives (leaders of data-driven functions) and Practitioners (early-career data scientists who drove the analysis workstream) who came up with their project ideas, sourced and explored datasets, and developed interesting analyses, insights and visualizations in just six weeks.
The Fellows produced 37 projects, and we are excited to share with you the four winning projects!
This team sought to understand city bike use in New York City by developing a model to predict bike under-supply. We were impressed by their novel use of data visualization, creating a working dashboard that immediately solves a real-world problem.
This group of Fellows sought to identify factors that make individuals more vulnerable to mental health issues. We were particularly impressed by their use of data visualization: their dashboard illuminates their analyses and identifies tactical opportunities for improvements to mental health care.
The team investigated data related to new traffic congestion zones in London and whether there were increases in pollutants and traffic levels specifically at the border of these zones. We would like to celebrate the impressive rigor of their data analysis.
Team members explored the use and role of prenatal care in US birth outcomes alongside demographic and socio-economic variables that predict its use. We were impressed by their thoughtful approach to a complex problem. Plus, their conclusions were clear, precise, and solutions-oriented.