Check out our website for everything you need to know: tamudatathon.com
A datathon is where you build your analytics skill set and create data driven solutions. We provide data science lectures, workshops, challenges, prizes, fun activities, swag, and more. We’ll take care of you while you learn & create!
Eligibility
TAMU Datathon is open to any enrolled undergraduate or graduate student who is at least 18 years of age, as well as people who have graduated within 1 year from the event. We welcome students from all across the world and from all majors!
Requirements
- All team members should have applied to TAMU Datathon on our website
- All submissions should be made through our Devpost: https://tamudatathon2020.devpost.com/
Prizes
$10,385 in prizes
1st Place TD Make-Your-Own Challenge
1st Place $400 x 4 team members
2nd Place TD Make-Your-Own Challenge
2nd Place $200 x 4 team members
3rd Place TD Make-Your-Own Challenge
3rd Place $100 x 4 team members
TD Stock Prediction Challenge
$500 x 4 team members
TD For-You Page Challenge
$400 x 4 team members
TD City Search Tool Challenge
$300 x 4 team members
MLH Best Domain Registered with Domain.com
PowerSquare Qi Wireless Phone Chargers & Domain.com Backpacks
MLH Best use of Google Cloud
Google Home Minis
1st Place Walmart Challenge
1st Place - Dell Monitors
2nd Place Walmart Challenge
2nd Place - Bose Speakers
3rd Place Walmart Challenge
3rd Place - Instax Instant Cameras
Capital One Challenge
$250 x 4 team members
Mathworks Challenge
$125 x 4 team members
HPE Challenge
(2)
Raspberry Pi 4 Starter Kits
Devpost Achievements
Submitting to this hackathon could earn you:
Judges

James Caverlee
Professor of Computer Science and Engineering

Darren Homrighausen
Associate Professor of Statistics

Dylan Shell
Professor of Computer Science and Engineering

Yang Shen
Assistant Professor, Electrical & Computer Engineering

Eric Zavesky
AT&T

Shreya Punya
Facebook

Brandon Walker
IBM

Humza Jaffri
TAMU Hack
Judging Criteria
-
Purpose
Communicated a clear understanding of the problem -
Framework
Mapped the task to a Data Science problem -
Data Use
Effectively used data, acquired additional data -
Models & Analytics
Effective application of analytics -
Validation
Assessed quality of solutions & models -
Impact
Clear description of the impact the solution has on solving the problem -
Presentation
Effectiveness, Engagement and Team Performance
Questions? Email the hackathon manager
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