09-19, 12:05–12:40 (Europe/Amsterdam), Rembrandt
First experience of stepping into the rabbit hole of contributing to open-source software, highlighting key learnings and practical steps for beginners. It covers overcoming self-doubt, learning through collaboration, and the unexpected joys of community engagement. What you can learn from contributing to Open Source and what you probably will not as an aspiring Data Scientist.
Prior Knowledge Expected & Audience:
This talk is aimed at aspiring contributors, autodidacts, students and anyone curious about the OSS ecosystem. It can be interesting both for Data Scientists as software engineers, but no prior knowledge is expected
Data and machine learning enthusiast with a soft spot for open-source software.
Driven by curiosity, eager self-learner, Kaggle Notebook Expert, Datathons enjoyer, PyData volunteer, currently engaged in Women in AI Mentorship, exploring and contributing to Open Source Land and building my Machine Learning portfolio.