Women in Data Science (WiDS)
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WiDS Datathon

Hone your data science skills with the WiDS Datathon, joining teams in a social impact challenge. The WiDS Datathon 2023 challenge will be announced this fall.

WiDS Datathon 2022 Highlights


​The WiDS Datathon is an initiative to provide a platform for data science enthusiast to learn, apply and hone their data science skills through the social impact challenges presented to them. Participants are trained and mentored by partners, ambassadors, and data enthusiasts.

In this short video, watch how the WiDS Datathon has evolved over the past fours years and an insight on the 2022 challenge that was focused on climate change.

WiDS Datathon 2022:
​Using Data Science to Mitigate Climate Change

The WiDS Datathon 2022, organized by the WiDS Worldwide team, Harvard University IACS, and the WiDS Datathon Committee, tackled a key way to mitigate the effects of climate change with a focus on energy efficiency. The WiDS Datathon Committee partnered with experts from many disciplines at Climate Change AI, Lawrence Berkeley National Laboratory (Berkeley Lab), US Environmental Protection Agency (EPA), and MIT Critical Data.​ WiDS Datathon participants analyzed regional differences in building energy efficiency, creating models to predict building energy consumption. 

WiDS Datathon 2022 Impact

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Registrants

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Read more

Congratulations WiDS Datathon Excellence in Research Award Winners!


The WiDS Datathon Phase II garnered participants from over 39 countries. Teams who submitted papers cross-collaborated throughout Antigua, Canada, France, India, Nigeria, Peru, Saudi Arabia, Spain, Trinidad and Tobago, and the US. Read stories and research papers shared by the winners.
Read more
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How it Works and Who Can Participate

The WiDS Datathon 2023 will be open from January - March 2023. Details and registration will be announced, this fall!

The dataset and challenge is accessible to both beginners and experienced participants. We release a series of resources to help you get started with the algorithms and dataset. Many WiDS ambassadors will host datathon workshops, where participants can to receive mentorship, form teams, and hone their data science skills. ​

The WiDS Datathon is open to individuals or teams of up to 4; at least half of each team must be individuals who identify as women. Participants can be students, faculty, government workers, members of NGOs, or industry members. You can form your teams directly on Kaggle.

WiDS Datathon Phase I Winners share their results ​
​and tell their stories:

Usha Rengaraju, Jerome Dadu, Mathurin Aché, and Zeineb Gnrib (India and France)
Kim Montgomery
(Colorado, USA)
Emily Osborn, Cheng Zhang, Heidi Cronkright, Chloe Bruce (Colorado, Maryland, Illinois, USA)

Host a datathon workshop to bring the WiDS Datathon 2023 to your cohort, colleagues, or community!

Learn More

​The WiDS Datathon is a collaboration led by the WiDS Worldwide team at Stanford University, WiDS Datathon Partners, and the WiDS Datathon committee. 
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​Made possible by the WiDS Global Visionary Sponsors:

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© 2023 Women in data science. Women in Data Science is a Registered trademark of Stanford University. 

  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Research
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conferences
    • WiDS Regional Events 2023
    • WiDS Stanford 2023 Online
    • WiDS Stanford 2023 Agenda
    • WiDS Stanford 2023 Speakers
    • Ambassadors 2023 >
      • Ambassador Advisory Council
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2023
      • WiDS 2022
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
  • Datathon
    • Datathon Details
    • Datathon Resources >
      • Datathon Press Release
    • WiDS Datathon Workshops 2023
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Next Gen >
      • Next Gen Resources
      • Next Gen Committee