NeuroLearn AI: Adaptive Learning Path Generator

Track

Creative Apps (GitHub Copilot)

Project Name

"NeuroLearn AI"

GitHub Username

@anusrisingaravel

Repository URL

https://github.com/anusrisingaravel/NEUROLEARN-AI

Project Description

Project Description: Briefly summarize that your app acts as an intelligent study companion that breaks down complex technical subjects into 7-day, milestone-based learning paths to reduce cognitive load.

Demo Video or Screenshots

https://www.loom.com/share/d982b94f956c49d7aaeb683db99e01c2

Primary Programming Language

Python

Key Technologies Used

Python, Streamlit, and any specific Azure or AI libraries.

Submission Type

Individual

Team Members

Submission Requirements

• My project meets the track-specific challenge requirements
• My repository includes a comprehensive README.md with setup instructions
• My code does not contain hardcoded API keys or secrets
• I have included demo materials (video or screenshots)
• My project is my own work with proper attribution for any third-party code
• I agree to the Code of Conduct
• I have read and agree to the Disclaimer
• My submission does NOT contain any confidential, proprietary, or sensitive information
• I confirm I have the rights to submit this content and grant the necessary licenses

Quick Setup Summary

Clone the repo.

Install dependencies (pip install -r requirements.txt).

Run the app (e.g., streamlit run app.py).

Technical Highlights

the implementation of your 7-day milestone logic and the use of an agentic approach for study planning.

Challenges & Learnings

"My biggest challenge was ensuring the AI didn't hallucinate when breaking down complex algorithms. I solved this by implementing a grounding mechanism with Foundry IQ, ensuring the 7-day plan is strictly based on the provided technical documents."

Contact Information

anusrisingaravel7@gmail.com

Country/Region

india

This issue describes a submitted NeuroLearn AI project rather than a specific change. Start with README.md, requirements.txt, and app.py; install the listed dependencies and run streamlit run app.py to inspect the application. No concrete acceptance criteria or requested modification is provided, so completion cannot be determined from the issue alone.