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!
We will be providing datasets, including, but not limited to, data from our sponsors. While at least one of our provided datasets has to be a central part of your project, you are free to use external data as well. The use of common data ensures a level playing field for all applicants, and encourages you to try different approaches with data you are not yet familiar with - a crucial skill for any data scientist :)
Sat, March 4 at 10:00-11:00am (MacMillan 117)
The explosion of clinical data provides an exciting new opportunity to use machine learning to discover new and impactful clinical information. Among the questions that can be addressed are establishing the value of treatments and interventions in heterogeneous patient populations, creating risk stratification for clinical endpoints, and investigating the benefit of specific practices or behaviors. However, there are many challenges to overcome.
Come and learn about how machine learning could change health!
Sat, February 25 at 2:00-3:00pm (Wilson 102)
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.
Sat, March 4 at 11:00am-12:00pm (MacMillan 117)
TripAdvisor is the world’s largest travel site, enabling travelers to unleash the potential of every trip. TripAdvisor offers advice from millions of travelers, with 435 million reviews and opinions covering 6.8 million accommodations, restaurants and attractions, and a wide variety of travel choices and planning features — checking more than 200 websites to help travelers find and book today’s lowest hotel prices. TripAdvisor branded sites make up the largest travel community in the world, reaching 390 million average unique monthly visitors in 49 markets worldwide.
TripAdvisor: Know better. Book better. Go better.
Sat, March 4 at 1:00-2:00pm (Smith-Buonanno 106)
Check out Daniel's workshop via Github here!
Sat, March 4 at 2:00-3:00pm (Smith-Buonanno 106)
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!
Check out Albie's workshop via Github here!
Sat, March 4 at 4:00-5:00pm (Smith-Buonanno 106)
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!
Sat, March 4 at 5:00-6:00pm (Smith-Buonanno 106)
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.
Sun, March 5 at 10:00-11:00am (Smith-Buonanno 106)
All computers on campus have R on them. In this workshop, participants will get familiar with simple features of the R language, and understand the ease at which data can be visualized in R. We will be utilizing ggplot2 a graphing package and Shiny R in order to make our visualizations interactive. This workshop is open to all, regardless of concentration, background, or experience level. People with no experience with coding who want to be able to apply some visualization/data science techniques to their non-CS classes are especially encouraged to come.
Sun, March 5 at 2:00-3:00pm (Smith-Buonanno 106)
What's swept under the rug? Every company does data science to some extend. Some do more systematically then others, but unfortunately this is not a common practice. We can attribute this to the intrinsic problem of data science: Dependency to data. I'll showcase some of the bad practices and the impacts of these practices in the long run. I'll also share some anecdotes on how to avoid them.
Sun, March 5 at 11:00am (Smith-Buonanno 106)
We are undoubtedly in the middle of an Analytics Revolution that enabled turning huge amounts data into insights, and insights into predictions and actions. In this talk, I would like to present an overview of the analytics landscape in the global enterprise and share some successful commercial showcases. I would also like to open a discussion on various challenges faced during the life-cycle of decision support system
Check-in at MacMillan Hall lobby.
Happening at MacMillan Auditorium (117).
Check it out at MacMillan Auditorium (117).
Find teammates in MacMillan Auditorium (115).
Get started in Smith-Buonanno.
Grab lunch in MacMillan Hall lobby.
All workshops are held in Smith-Buonanno (106).
Dinner is in Smith-Buonanno lobby.
Grab food in Smith-Buonanno lobby.
All workshops are held in Smith-Buonanno (106).
Get food in Smith-Buonanno lobby.
Announced in Smith-Buonanno (106).