Prototype Sprint – Build, Test, Improve

The Prototype Sprint aimed to help students transform their ideas into functional AI-based prototypes through an intensive cycle of ideation, development, and refinement. Teams worked collaboratively on real-world problem themes relevant to industry trends, receiving continuous guidance from faculty mentors to improve design, usability, and functionality.

Following an iterative approach of “build, test, and improve,” students engaged in coding, debugging, and optimization, fostering creativity and technical skills. The event emphasized critical thinking about user needs, data-driven decision-making, and ethical AI practices, preparing students for real-world challenges.

Participants gained confidence in turning abstract concepts into tangible prototypes and learned the value of iteration and feedback. The experience enhanced their technical proficiency, problem-solving abilities, and teamwork skills.

Feedback highlighted the event’s effectiveness in connecting classroom knowledge with practical innovation. The Prototype Sprint reinforced the department’s commitment to experiential learning and nurturing future-ready AI and Data Science professionals.