Invent:YU provides a unique forum for computer science and data science students, many whom are Jewish, to connect, brainstorm and partner together over a 24-hour period. Unlike other Hackathons, the YU Hackathon does not take place on Saturday, allowing Shabbat observing students to participate in an exciting event that generally would not be open to them.
The theme for this year's program is “Giving Back”, focusing on solving problems that non-profit organizations may face in their day to day operations.
Our Hackathon has two dual tracks: a standard Hackathon track, featuring CS/Engineering projects, and a Data Science track.
Students do not necessarily need a coding background to participate or enjoy. We are just looking for students who have an interest in science, technology, and using their minds to create.
Please see the Rules tab for more details.
The event is open to students between the ages of 16-26.
$2,318 in prizes
Best Domain Name Registered With Domain.com
Raspberry Pi & PiHut Essential Kit
Best Use of Amazon Web Services
$250 Amazon Web Services Credit (US ONLY)
First Place Prize
$2,000 towards a Charidy Campaign
Second Place Team
1 LiteCoin (to split between team members)
Submitting to this hackathon could earn you:
Professor at Yeshiva University
Master Principal Enterprise Cloud Architect at Oracle
Director of Data and Evaluation at NCSY
Major League Hacking
Hacking Track: Problem Definition
How precise and relevant is the real world problem or opportunity? How interesting or difficult to resolve - functionally or technically - is the problem being challenged?
Hacking Track: Solution Design & Innovation
Does the application approach a new problem, or look at an old problem in a new way? Is the solution innovative or does it rely on an existing tech? To what degree does the application actually solve the problem?
Hacking Track: Idea Viability
Is the application marketable? Would people use this product? Is this solution only theoretical or does it have a realistic application for commercial purposes?
Hacking Track: Functionality
Does the prototype work? Is it user-friendly? Is the design visually appealing?
Data Analysis Track: Relevance
How precise and relevant is the real world problem or opportunity?
Data Analysis Track: Value of Insight
How valuable and relevant is the insight presented?
Data Analysis Track: Quality of Analysis
How incisive is the analysis? What is the level of quality of the analysis? Does the code follow both programming and statistical rigor?
Data Analysis Track: Creativity