🌟 Internship Program Analysis 🌟 This project explores key trends in internship opportunities across various companies and roles. Using Python (Pandas, Matplotlib, Seaborn), the dataset was cleaned, analyzed, and visualized for insights. It highlights top internship titles, locations, durations, and stipend patterns.

Practice and guided data analysis projects focused on applied learning, dashboard development, and data storytelling

This project demonstrates data cleaning on the Nashville Housing dataset (2013–2016) using R and packages like tidyverse, lubridate, and janitor. Key steps included standardizing column names, handling missing values, formatting dates, cleaning text fields, and identifying outliers. The cleaned dataset is now ready for analysis and modeling to unco

📊 Analyze internship listings to reveal trends, skills in demand, and opportunities, transforming raw data into actionable insights for students and organizations.