2017 Columbia Data Science Hackathon

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About

The Columbia Data Science Society is proud to host the third annual 2017 Columbia Data Science Hackathon. We are excited to see what you can do in collaboration with other students using datasets provided by our corporate sponsors. To help you gear up, we’ll be hosting workshops leading up to the event and will connect you with data science mentors from industry at the hackathon.

The hackathon will suit students with a background in Computer Science, Data Science, Engineering, Statistics, Analytics and Math. Students from all universities are welcome! 

The top 3 teams will win $3,000, $2,000, and $1,000 in cash prizes!


Sponsors

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Learning Resources

Food

Additional learning resources will be provided soon in the form of online material and on-campus workshops.

Dinner, breakfast, lunch, and plenty of snacks will be provided throughout the event!


 

Where

Roone Arledge Auditorium
Lerner Hall Floor 1W
Columbia University
New York, NY 10027

When

Friday, September 22, 2017
Start: 4 pm
Saturday, September 23, 2017
End: 2 pm

 

Schedule

 
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FAQ

Do we form our own teams, or does CDSS assign them?

You'll form your own dream team! If you don’t know anyone prior to the hackathon, no worries. You’ll have plenty of time during the ramp-up workshops and dinner to meet other students and find a team by 9 pm Friday!

How can I prepare for the hackathon?

Brush up on your data exploration, modeling, visualization, and presentation skills. Here’s a great self-paced data science tutorial in Python.

We’re also holding a pre-hackathon workshop on Tuesday, September 19 from 8-9 pm that will cover how to use Google Cloud Platform and/or a data science case study. Stay tuned for more info!

How many students can work together on a team?

2 - 4.

Can I work alone?

No, this is meant to be a team effort!

What makes a successful hackathon project?

Glad you asked! Successful projects usually have a mix of modeling and data visualization, and good presentations always clearly communicate the analysis, results, and impact. The judges want to see that you’re thoughtful about the problem at hand, effective in executing your analysis, and compelling when talking about why your project matters.

How will hackathon projects be evaluated?

Everyone will participate in an initial round of short presentations, then teams that are selected as finalists will give longer presentations of their work. The hackathon will be open-ended — we will provide suggested data problems to work on, but this is no Kaggle competition — so you’ll get to work on whatever you find most interesting. Project evaluation is not based on achieving 95% model accuracy but rather how you choose to credit an impactful model and analytical framework to answer a question about data.


Previous Hackathons


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