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UC Berkeley AI Hackathon 2026

devpostHosted on Devpost

Fetched about 4 hours ago

Saturday, June 20, 2026

to Sunday, June 21, 2026

•

1 day long

Artificial IntelligenceData ScienceWeb Development
Student only
This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.

Event Type

in person

144

Participants

12

Est. Projects

UC Berkeley's AI Hackathon is back! Hackathons @ Berkeley, the team behind Cal Hacks, will be bringing you two days of hacking on the best AI technology the world has to offer. With support from Annapurna Labs, Fetch AI, and more, this will be a monumental event no future AI/LLM developer can afford to miss. You'll even have chance to pitch your project to investors, and win cash prizes! This event is your chance to explore the potential of large language models and other open source APIs, all while making a lasting impact in the world of artificial intelligence.

Note: Applications to the UC Berkeley AI Hackathon have closed and accepted + confirmed hackers have been reached out to via email. If you just found out about this event, please sign up for our mailing list on our website to be the first to hear of our future events!

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct