Work around the clock to discover and share insights about large, rich, and complex data sets with a team of other undergraduates! Hosted by Brown Data Science.
Datathon is a celebration of data in which teams of undergraduates work around the clock to discover and share insights about large, rich, and complex data sets.
The event is sponsored by the Computer Science Department and the recently launched Data Science Initiative at Brown University. The Data Science Initiative is a cross-departmental program that aims to develop and promote data-driven research and education on campus.
Apart from the competition itself, which is the core of the event, there will be many other supporting activities ranging from educational workshops to opportunities to network with peers and industry representatives.
$21,200 in prizes
Grand Prize: Sponsored by Goldman Sachs (2)
A tote bag with a hoodie, a water bottle, ***an iPhone X***, and an invitation to present your winning findings to senior staff in Engineering at Goldman Sachs HQ in New York—all expenses paid for each team member.
Neo smartpen + Notebook for each team member
Google Home for each team member
Submitting to this hackathon could earn you:
We welcome students from anywhere, and will do our best to reimburse you for transport. Amtrak or MBTA will get you to Providence Station, just a ten minute walk from Brown’s Campus.
Director at Brown Data Science Initiative; Brown Computer Science Professor
Data Scientist at Upserve
Brown Computer Science Professor, Fidelity
Brown Economics Professor; Brown Data Science Initiative
Brown Physics Professor
Postdoctoral Research Assistant at Brown University
Brown Statistics Professor
Brown Statistics Professor
Quality of the overall approach will be prioritized irrespective of which dataset is chosen or product created (result, visualization, tool, etc.). Marks of quality could include robust features, versatile and readable code, and polished presentation.
Datasets do not come with explicit problem statements. Creativity will be rewarded where it provides new insights or unique applications while still being tied to one or more datasets and is grounded in reality.
The composition of a team will be taken into account when judging a project. A project completed by undergraduates is more impressive than a similar project done by a team of PhD candidates. We encourage diversity of experience and background in teams.
Complete projects will be held in higher regard than incomplete projects; however, the potential that an insight or application shows will be taken into account, including if it is not complete. Submit your project, anything counts!