Explore beginner-friendly and real-time Data Science projects using Python, Pandas, NumPy, and data visualization tools.
Use K-Means clustering to group customers based on their purchase patterns and behaviors.
Build a regression model to predict housing prices using datasets with area, location, and other features.
Analyze stock price data and visualize trends using Matplotlib and Seaborn to understand market movement.
Analyze global Covid-19 datasets to understand trends, growth rates, and impact using Pandas and Plotly.
Predict future sales using time-series forecasting models such as ARIMA or Prophet.
Analyze tweets or posts to determine whether public sentiment is positive, negative, or neutral.
Use classification algorithms to detect fraudulent transactions from credit card datasets.
Predict which employees are likely to leave the company using logistic regression and feature analysis.
Build a simple recommendation system based on user ratings and browsing history.