This project is not just about deliverablesโitโs about growing as data scientists and collaborators. We define individual and collective learning goals to maximize the benefit of this experience.
Each team member is encouraged to:
- Identify 1โ2 technical skills to focus on (e.g., feature engineering, model selection, data visualization).
- Identify 1 collaborative or soft skill (e.g., presenting results, giving feedback, managing time).
As a team, we aim to:
- Practice collaborative coding using Git and pull requests.
- Build reproducible workflows and document our processes clearly.
- Improve data storytelling and communication of results.
- Embrace feedback and peer learning to continuously improve.
- At the end of each milestone or sprint, we conduct a short learning reflection session.
- Members share what they learned, what challenged them, and how they grew.
We view constraints not as limitations, but as frameworks for creativity.
Through clear communication and shared learning goals, we grow strongerโas individuals and as a team.