You're about to be part of something big: a 2-day hackathon where you'll build AI solutions on Databricks, collaborate with brilliant minds, and compete for prizes. This guide has everything you need to hit the ground running. Read it, prep your tools, and come ready to build!
Requirements
- A public GitHub repo with an architecture diagram showing how Databricks components connect. Must remain public for at least 30 days. README must include: what it does (1-2 sentences), architecture diagram, how to run (exact commands), and demo steps (what to click / what prompt to run).
- A project write-up: up to 500 characters describing what you built and why.
- Which Databricks technologies and open-source models you have used.
- A demo video: up to 2 minutes showing the solution in action.
- A link to a deployed prototype.
Judges will attempt to reproduce your demo from the GitHub repo. If it doesn't run, it doesn't score.
Optional / Bonus- BhashaBench evaluation scores
- MLflow experiment logs
- Quantitative accuracy metrics
Prizes
1st Place
+ special Databricks swag
2nd Place
+ special Databricks swag
3rd Place
+ special Databricks swag
Devpost Achievements
Submitting to this hackathon could earn you:
Judges
Soumyashree Patra
Databricks
Vishesh Arya
Databricks
Ashveen Bansal
Databricks
Preksha Punwani
Databricks
Judging Criteria
-
Databricks Usage
Depth and correctness of platform usage. Is Delta Lake/Spark actually doing work, or just present? Bonus for creative use of multiple components. -
Accuracy & Effectiveness
Does the AI actually work? Are the techniques sound and the results verifiable? -
Innovation
Is the problem well-chosen? Is the solution novel? Does it address a real Indian context in a non-obvious way? -
Presentation & Demo
Can you explain what you built, why you built it, and how it works, clearly and confidently in under 5 minutes?
Questions? Email the hackathon manager
Tell your friends
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
