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SunnyHacks June 2026

devpostHosted on Devpost

Fetched 7 days ago

Monday, June 1, 2026

to Wednesday, July 1, 2026

•

1 month long

Data ScienceArtificial IntelligenceWeb 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

online

70

Participants

6

Est. Projects

SunnyHacks is a student-led hackathon focused on AI agents: systems that can reason, make decisions, and take actions on their own. The event brings together students from a range of technical and academic backgrounds to explore how these systems can be designed, applied, and used in real-world setting. Recent advances in large language models and tool-integrated AI have shifted attention from static models to more dynamic systems capable of multi-step problem solving. SunnyHacks is designed to give students direct exposure to this shift, encouraging them to go beyond simply using AI and instead build systems that can tasks with minimal human input. Heavy use of AI in the development process to generate code is discouraged :(

Sponsors

CodeCrafters image

CodeCrafters

codecrafters.io

Wolfram Language image

Wolfram Language

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