The first MLH Data Science Hackathon in the world!
For the first time, TAMU Datathon is banding together data enthusiasts from across multiple disciplines, skill levels, and universities. TAMU Datathon is a 24-hour event where companies, researchers, and hundreds of students immerse themselves in data science.
We’re coming together to solve real-world challenges, learn about data science, hear from leaders in research, and compete for company and university prizes.
This all happens in a fun, interactive, and competitive way by providing our participants the option to take part in the Learner Track or the Competitor Track. We believe the TAMU Datathon will inspire students across all disciplines to integrate quality data-driven practices into their field of expertise.
$13,560 in prizes
- 1st Place: Oculus Quest All-in-one VR Gaming Headset (64GB)
(Plus, an opportunity of working towards the next “State of the Map” Conference)
- Oculus Quest All-in-one VR Gaming Headset
- Powerbeats Pro 3
- JBL Flip 5
(1st place gets first pick of prizes, 2nd gets next pick, 3rd gets remaining prize)
- 1st Place: Amazon Echo
1st Place: Amazon Echo Show
- 1st Place: Shell Goodie Bags & 50$ Shell gift-card
- 1st Place: Bose headsets
- 2nd Place: Go Pros
- 3rd Place: Instant cameras
Best use of Google Cloud
Google Home Minis for each team member
Best Domain Name from Domain.com
Domain.com branded backpack for each team member.
Best Automation Hack with UiPath
Build an automation hack using UiPath! Each winning team member will receive a UiPath/MLH Branded Backpack and DROCON Drone!
Submitting to this hackathon could earn you:
- Applicants that have RSVP'd to the event invitation
- Teams or Individuals
- Any major from any university
- Freshman to Ph.D. students
- Host country - United States
- Available to any country
Communicated a clear understanding of the problem
Mapped the task to a Data Science problem
Effectively used data, acquired additional data
Models & Analytics
Effective application of analytics
Assessed quality of solutions & models
Clear description of the impact the solution has on solving the problem
Effectiveness, Engagement and Team Performance
- Machine Learning/ AI