AI For Social Impact Hackathon 2025
Innovate. Collaborate. Transform the World with AI.
Solve real-world challenges with AI and data science while networking with top talent, mentors, and industry leaders.
Hackathon Holds in
The AI for Social Impact Hackathon 2025 is a dynamic two-day event designed to bring together innovators, problem-solvers, and enthusiasts from the fields of data science and artificial intelligence. Whether you’re a beginner eager to learn or a seasoned professional looking to showcase your skills, this hackathon provides a unique platform to collaborate, create, and make a difference.
Who can Participate?
From AI beginners looking to learn to advanced practitioners ready to innovate.
Students, professionals, and enthusiasts with an interest in data science, machine learning, AI, and related fields.
Teams of 3-5 members are encouraged to ensure a mix of skills and ideas. Solo participants will have the chance to join a team during Day 1's networking session.
Tackle real-world challenges, expand your network, sharpen your skills, and gain recognition—all while making a meaningful impact through AI innovation.
Challenge Examples for the AI for Social Impact Hackathon
Education
Personalized Learning Pathways:
- Goal: Develop an AI model that adapts learning materials to individual student needs and learning speeds.
- Dataset: Student performance data from online learning platforms.
- Impact: Help bridge the gap in education quality for underserved communities.
Security
AI-Powered Threat Detection:
- Goal: Design a system to detect phishing emails or malicious links in real-time.
- Dataset: Public datasets of phishing websites and emails.
- Impact: Enhance cybersecurity for individuals and small businesses.
Health
AI Mental Health Support:
- Goal: Create a chatbot that provides mental health resources and empathetic support for individuals in distress.
- Dataset: Publicly available mental health-related conversations.
- Impact: Increase access to mental health support.
Governance
AI for Transparent Elections:
- Goal: Develop a tool to analyze election-related data for signs of anomalies or misinformation.
- Dataset: Historical election results, social media trends, and news coverage.
- Impact: Promote transparency and trust in electoral processes.
Community and Social, Responsibility
Disaster Relief Coordination:
- Goal: Build an AI model to predict areas most in need of relief during natural disasters.
- Dataset: Historical disaster data and satellite imagery.
- Impact: Improve disaster response and save lives.
