Brown Datathon

March 4-5, 2017

@ Providence, RI

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.


Who can attend?

Anyone who is a high school, undergraduate or graduate student can attend Datathon. No experience with data science is assumed. There will be workshops and speakers that students of any background can learn from!

What if I don't have a team?

You can still participate in Datathon even if you don't have a team. You can also form a team at the event during one of our team-forming sessions! A team can consist of a maximum of four people.

What should I bring?

You should bring your laptop, phone, chargers and sleeping equipment!

I’m not a Brown student. Can I still participate?

Absolutely! 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.

How much is this going to cost?

Datathon is 100% free. We will be providing free food, drinks, and swag!

Other questions?

If you have any more questions or concerns feel free to email us at: You can also check out our Facebook page.

Keynote Speaker

Marzyeh Ghassemi

MIT Computer Science Artificial Intelligence Laboratory; PhD Candidate

Why Machine Learning Should Change Health

The explosion of clinical data provides an exciting new opportunity to use machine learning to discover new and impactful clinical information. However, there are many challenges to overcome.


Intro to D3.js

Daniel Kunin, Brown '17, APMA-Bio

D3.js is an extremely powerful JavaScript library for web-based data visualization. It is used by companies such as the New York Times and FiveThirtyEight and has created some of the most beautiful and elegant data visualizations on the web. We will be go through the basic structure of a D3.js visualization and work on a couple short demos as a group. No experience necessary.

The Impact of Data Analysis on the World of Sports

Colby Tresness, Brown '17, APMA-CS

The Sports Analytics Workshop will focus on how data can be leveraged to drive new insights in sports for front offices, coaching staffs, and fans. We will touch on key figures in the sports analytics community and the role of data science in the industry.

As a group, we will then explore how to predict future NBA career success of college basketball prospects and the many challenges that come with this endeavor. This workshop is open to all, regardless of concentration, background, or experience level!

Apache Solr

Martin Zhu, Brown '17, CS

We will look at how to perform full text search on large datasets in real time.

Introduction to Deep Learning with Tensorflow

Sidd Karamcheti, Brown '18, CS and Literary Arts

Deep neural networks have been utilized to obtain state-of-the-art results in several problems in computer vision, natural language processing, and speech recognition. In this workshop, learn how to use the popular framework Tensorflow to quickly prototype deep neural network models. We'll be covering the basics of feed-forward networks, convolutional neural networks, and recurrent neural networks.

Assumes experience/coursework in linear algebra, probability, and general machine learning.

Data Analytics in Healthcare

Grant Fong, Brown '19

With the massive increase in data being produced in the healthcare space, new insights are constantly being discovered. This workshop will explore what sorts of datasets are available, and what some of the best practices are when coming to analyzing health data.

Intro to Web Scraping by Spotter (using Beautiful Soup)

Albie Brown @ Spotter, Brown '16

Is your hand still sore from copy-pasting for hours? Ever wished you could just download the internet? Hang out with the Spotter team and learn to turn websites into datasets. We'll teach you how to use the Beautiful Soup library to start you off on your web-scraping journey. Beginners welcome!