About the Rowdy Datathon
The Rowdy Datathon is a free, weekend-long, overnight hackathon focused on data science where students can network, learn about data science, code, and collaborate!

Team up with other students to tackle a data science challenge for a chance to win prizes! Mentors will be available to help you work through the challenge! Attend workshops, mini events, socials, and network with our industry partners!

Attendance is FREE and all meals, snacks, and drinks are provided. We welcome students from all disciplines, backgrounds, and technical levels! 

We’re excited to announce you’ll be wranglin’ some education data this year!
We are embracing our Texan roots to give you a western-themed weekend where all our participants, Data Wranglers, can provide insights and advice on critical challenges facing our education system.

We’ll give you everything you need
No need to prepare your own dataset or project idea. We will give all participants the same dataset to use for our challenge.

No Experience Necessary
To help you navigate the challenge, learn data science skills, and make the most of the weekend, we will provide mentors and workshops. We will also have tracks for beginner, intermediate, and advanced data scientists. The focus of this event is to foster your growth and excitement for data science.

Wrestle up a team or wrangle solo
We will have a team-building mini event to help you find your dream team. If you choose to team up beforehand, remember that the challenge will require mathematics, statistics, data ethics, AND computer science knowledge, so go multi-disciplinary if you can!

• Skill Level
  The level of inquiry must be proportional to skills. A participant who claims a lower level of expertise could be disqualified.
• Compelling Presentation
  Share your numerical and graphical results with legislators through executive summaries that are understandable and convincing. Express actionable results e.g. funding schools, care for elderly, etc. Supporting documentation can be technical.
• Analysis Comprehension
  Before a single line of code is written, before a single byte of raw data is processed, you must be able to tell the story of what is the progression of steps that will be undertaken in analysis.
• Sound Technical Methods
  You may cite the analyses of others, but we want to see the methods that you have invented or adopted to calculate these projections (accompanied by error bars, if possible). The commission must have confidence in your results.
• Awareness of the Data Context
  All data have bias. Before, during and after analysis, it is essential to identify biases in the data and articulate clearly how these biases influence all steps of analysis and interpretation.
• Reproducible Results
  You must enable the commission to have your results confirmed by an independent team. That is, enable the independent team to replicate your results by describing your data and methods in detail.
• Growth
  Showcase what you knew before this weekend and what you learned. Share difficulties and successes, but it should be evident you tried something new.