WiDS Datathon challenges are based on well-curated, real-world datasets that are not readily available in the public domain. Competitions are hosted on Kaggle and teams are required to have at least 50% women. Participating in a WiDS Datathon is a fantastic opportunity for students to gain experience and see an application to a real and critical challenge! Learn about this year’s challenge tasks.
Bring the WiDS Datathon to your classroom!
Attend a meetup to find out more. The next instructor meetup will take place on October 12th
The Challenges
Colleges and universities can interact and work with the WiDS Datathon challenges in multiple ways:
WiDS Datathon
#1: January 9 – March 1, 2024
#2: April 9 – June 1, 2024
These challenges can be offered as a 1-unit course or project in undergraduate or graduate courses that provide a first entry to data science. Similar datasets will be used in both datathon sprints. You are welcome to participate in one–or both–sprints.
Audience: First entry to data science, data analytics, or machine learning
WiDS Datathon++
September 18, 2023 – June 30, 2024
This challenge, available only to colleges and universities, can be offered as a project in more advanced undergraduate or graduate courses. It can also serve as a capstone course, the base of an honors thesis, independent research, directed research, or a standalone 3-unit course. The challenge will be designed not just to support the competition, but also to prompt discussions to generate additional insights and to understand the real-world implications of the results.
Audience: Advanced students
The WiDS Datathon gave me the sense of how to handle such big datasets in data science. As I belong to the data science department at my college, I have a great project to work on because of this hackathon.
— Rutuja Thakra
Undergraduate Student
Why integrate the datathon into your course curricula?
- Provide a unique learning experience: integrate a hands-on project with unique data that is relatively unexplored, and in a fun, competition setting
- Access to data: well-curated and designed real–world data not available (therefore not accessible) to the public
- Enhance curriculum: incorporate different and collaborative ways to learn, with a potential to be used as a capstone project
- Broad applicability: options for both beginner and advanced level data science students
- Access to global community: expose students to diverse perspectives
WiDS Datathon Instructor Resources
We are excited to be a resource to help you and your students succeed! The WiDS Datathon team provides a variety of resources for educational instructors, including:
Implementation Guide
Easy step-by-step instructions and guidance about how to bring the WiDS Datathon to your course.
Tutorials and Class Resources
We will provide a kit of technical tutorials and skill-building materials.
Monthly Meetups & Community
Discuss best practices, bring your questions and interact with other course instructors and mentors!