AI Study Tracker & Priority Scheduler: Helping My Friend Ace Exams

A developer built a single-page AI Smart Study Planner & Timetable Scheduler for a friend preparing for exams, generating a prioritized revision timetable from exam dates, subjects, and difficulty concerns. The app runs entirely client-side in HTML5, CSS3, and JavaScript, using local inference heuristics that simulate zero-shot classification to rank topics by deadline and pain point without sending data to external APIs.

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend https://dev.to/challenges/hacktoberfest-weekend-2026-10-01 < -- 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 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