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.
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!
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.
You should bring your laptop, phone, chargers and sleeping equipment!
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.
Datathon is 100% free. We will be providing free food, drinks, and swag!
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.
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!
We will look at how to perform full text search on large datasets in real time.
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.
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.
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!