Skills Used: OOP fundamentals, time modules, and functions The Alarm Clock project demonstrates how coding can be used to solve real-world issues through a practical Python implementation. You will construct a digital alarm system in this project that enables users to program alarms for a given time and receive notifications when that time comes. The application continuously monitors and contrasts the alarm time with the system time using Python's time module. Functions are used for tasks like setting the alarm, checking the time, and triggering alerts in order to make the code more standardized and reusable. In order to apply OOP ideas like encapsulation and make the program more scalable and structured, an AlarmClock class is also implemented. Results: By finishing this project, you will have a Python-based alarm system that works flawlessly and shows how logic can be integrated with real-time events. This will help you better understand modular coding, object-oriented programming, and time-based programming.

The Birthday Reminder project is a simple yet useful Python-based application that helps users keep track of birthdays. Utilizing the datetime library, the program compares the current date with stored birth dates and sends timely reminders. Loops are used to iterate through the list of birthdays and check for upcoming events. The project can be enhanced by integrating file handling to store birthdays in a text file, JSON, or CSV format, allowing users to update and manage birthdays easily. Future improvements include adding an automated notification system via email or SMS and a user-friendly interface for better accessibility.

The Car Price Predictor project is a web-based application that allows users to estimate the selling price of used cars by inputting key details, such as mileage and year of manufacture. The application leverages a linear regression model, trained on historical data, to generate price predictions. Users can interact with the app easily, inputting their information to receive an estimated price instantly. Additionally, the underlying model is evaluated to ensure the accuracy and reliability of predictions. This tool offers valuable insights into how specific attributes, such as car mileage and model year, affect overall pricing trends. By using this application, users can make more informed decisions when buying or selling cars in the used car market. Future enhancements will incorporate more advanced predictive algorithms and additional data points to further improve accuracy and user experience. for 8 seconds The Car Price Predictor project is a dynamic web application designed to estimate the value of used cars by leveraging data science techniques. Users input vital vehicle details such as mileage, manufacturing year, and more, which are then processed using Python's data libraries. A linear regression model, developed with Scikit-learn, analyzes historical selling data to provide accurate price predictions. The model's performance is visualized with tools that highlight how different features impact the final price. With a user-friendly interface built on Flask, the application ensures seamless interaction and quick insights for both buyers and sellers. This project not only simplifies decision-making in the used car market but also sets a foundation for future enhancements by integrating additional data points and advanced algorithms

Skills: Python, Django Channels, JavaScript, API integration, and rule-based NLP Project Description: Create an AI-powered chatbot that helps students choose classes and plan their academic paths. This project shows how Fullstack AI and GenAI can be used in educational technology. It uses Django Channels for real-time messaging, JavaScript for an interactive front end, and NLP or API-based logic for smart responses. The system can answer questions on the fly, make suggestions, and help students make better decisions quickly. Outcome: Create a fully functional, real-time chatbot that helps students get better advice, makes personalized course recommendations easier, and makes academic planning as a whole more efficient.