WiDS
The WiDS datathon is a Stanford University initiative preceding the Women in Data Science Conference (WiDS) (to be held on 5 March 2020 in Maastricht). WiDS aims at inspiring and educating data scientists worldwide, regardless of gender, and supporting women in the field. The WiDS Datathon builds upon these same objectives by enabling a diverse team to work together in a data-related challenge. 

Stanford University as the initiator will release a data challenge on the Kaggle platform (www.kaggle.com). You can join the WiDS Datathon 2020 as an individual or with a team to tackle this data challenge competing with other teams from all over the world. Aligned with the mission of the Women in Data Science Conference, we aim to inspire women to learn more about data science and create a supportive environment for women in STEM domain in general. In the WiDS Datathon 2020, we mandate at least 50% women in each participating team.

This year's challenge
The WiDS Datathon 2020 focuses on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score)  initiative, with privacy certification from the Harvard Privacy Lab. This year dataset contains more than 130,000 hospital Intensive Care Unit (ICU) visits from patients, spanning a one-year timeframe. 

Participating teams need to create a model that predicts patient survival. Data analysis can be done using your preferred tools and submitted to Kaggle platform. The winners will be determined by the leaderboard on the Kaggle platform at the time the Datathon closes February 24. 

Please consult the detailed program of the WiDS Datathon 2020 here

Pre-training session 7 February
If you have not participated in Kaggle competitions before or if you do not have sufficient data science skills, please join our pre-training session in the afternoon of 7th February. We will help you to use Kaggle platform, understand the dataset, introduce data analysis pipeline, brainstorming on possible solutions, etc. This session will also serve as a warm-up for the Datathon. People who have experience in data science are also very welcome to join to help others and get to know your team members in Datathon.