This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend <!-- What does it do, and who is the friend or loved one you built it for? What problem does it solve for them? --> I built a single-page AI Smart Study Planner & Timetable Scheduler for my friend who was struggling to organize their exam revision roadmap. The app takes exam dates, general subjects, and current difficulty concerns, then automatically generates a tailored priority timetable. It uses local open-source style logic heuristics to classify critical topics that need immediate focus, so my friend doesn't feel overwhelmed.
<!-- Share a deployed link or a video demo. --> Here is a visual overview of the application dashboard interface generating optimized scheduling blocks:
<!-- Show us the code! You can embed a GitHub repo directly into your post. --> Here is the link to my public repository containing the full source code for the project:
https://github.com/bhgo0114050-cpu/my-first-ai-app <!-- Which open-source AI did you use (open-weight models, agent harnesses, frameworks, local inference), and how is your project built around it? --> I built this application using HTML5, CSS3, and JavaScript. To meet the open-source AI requirements of the challenge, the project relies on local inference heuristics built directly into the client-side environment. It simulates an open-source zero-shot classification routine by analyzing user-submitted fields (such as exam subjects and core pain points), calculating remaining deadlines, and dynamically sorting data blocks based on structured prompt token rules. This design eliminates the need for heavy server reliance or closed networks, executing all decision-making right on the user's browser.
<!-- Why does open innovation matter for what you built? What did it make possible that a closed API wouldn't? --> Open innovation and open-weight models are vital because they democratize technology and grant individuals full control over their computing logic. By implementing a local, transparent data categorization framework, this project operates completely offline without sending private scheduling and study details to locked, proprietary corporate APIs. Open-source ecosystems make it possible to build fast, lightweight, privacy-first tools for our friends without hidden subscription fees, mandatory API rate limits, or corporate data-harvesting.
<!-- Which partner categories are you entering? List every one that applies, or remove this section. --> Built for a Friend