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
392
Participants
35
Est. Projects
Organizers
Alex Johnson
alex@example.org
Jamie Rivera
jamie@example.org
Sam Chen
sam@example.org
Quality Score
Quality Score
72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
With over 11 successful Hackathon editions in past, Our Hackathon has already garnered 100,000+ impressions and 2500+ enthusiastic registrations. Back by popular demand, with the growing academic pressure on engineering students, this challenge focuses on building an intelligent, AI-powered study planning solution that addresses real-world learning problems faced during engineering education. The AI Study Planner challenge gives you the opportunity to design a system that helps students study smarter, manage time effectively, and reduce academic stress through personalized planning. About the Challenge: Build tools that help engineering students plan their studies effectively, focused on personalized, adaptive study schedules, designed specifically for engineering students, real academic problem with real student impact. Core Focus Areas: Intelligent study time allocation, cognitive load balancing across subjects, prerequisite and concept dependency handling, dynamic prioritization based on deadlines, personalized learning pace and constraints. What You’ll Work On: Creating a smart study planning system, generating adaptive daily/weekly study schedules, identifying weak areas and prerequisite gaps, optimizing study patterns for better retention, building a clean, easy-to-use planning interface. Prizes Worth Competing For: Winner: 50% Scholarship on Build4Hire – Web Dev Gen AI Program. First Runner-Up: 40% Scholarship on Build4Hire – Web Dev Gen AI Program. Second Runner-Up: 30% Scholarship on Build4Hire – Web Dev Gen AI Program. Bonuses for Participants: Special Bonus: AI prompts used by top engineer, Free Certificate for every valid submission from UnsaidTalks. Learning Outcomes: By the end of this challenge, participants will gain experience building adaptive AI-powered planning systems, understanding of cognitive load-aware scheduling, skills in designing personalized productivity tools, confidence handling real-world academic constraints, a strong project demonstrating practical problem-solving.