SchedulEase-IITK-course-planner-recommender

Welcome to SchedulEase-IITK (Schedule with Ease IIT Kanpur), a web application designed to simplify course timetable management. Whether you're dealing with course conflicts or trying to organize your schedule, this tool offers an intuitive interface to help you manage your academic life at IIT Kanpur.

Description

SchedulEase-IITK is designed to help IIT Kanpur students efficiently create their academic schedules. It automatically navigates over 700+ courses from 20+ departments, ensuring that no selected courses clash. Built with a Flask backend, it offers comprehensive course coverage and simplifies the scheduling process, making it easy for students to avoid conflicts and create their ideal timetable.

Motivation: At IIT Kanpur, competitive programming can overshadow practical coding, creating an isolating environment. SchedulEase-IITK was developed as a side project to channel my passion for coding into something valuable for my peers, highlighting that coding is not just about competition but also creativity and problem-solving.

Setup

1. Clone the repository

git clone https://github.com/rkaran04/SchedulEase-IITK-course-planner-recommender.git

It is optimised to run with debugging off on your local server, you can change by modiying app.py

2. Prepare Course CSV

Please follow the steps mentioned here to procure the course data from here and place it in the cloned repository

3. Update data (if needed)

bash update_data.sh

Run the above code to update the .json files

4. Run the Server

bash launch.sh

Run the above code to view the web-app work on http://127.0.0.1:5000/

Project Structure

SchedulEase-IITK  
├── ASSETS/  
├── BACK_END/  
├── Extract_course_data/  
├── FRONT_END/  
├── RECOMMENDATION/  
├── Course_schedule_from_pingala.csv    
├── updata_data.sh                      
├── launch.sh                           
└── README.md  

Key Folders and Files

• ASSETS/: Contains courses.json and details.json for managing course data.
• BACK_END/: Handles core backend logic, including app.py and course_schedule_manager.py.
• Extract_course_data/: Contains scripts for converting course data from CSV to JSON format.
• FRONT_END/: Includes index.html, styles.css, and scripts.js for the frontend design and functionality.
• RECOMMENDATION/: Contains code for course recommendation based on user input.