World University Student Survey Dataset

This dataset contains synthetic survey data of 1,000+ students from universities worldwide, designed for data analysis, visualization, and machine learning projects. It provides a comprehensive view of student demographics, academic programs, tuition fees, scholarships, learning modes, campus facilities, teaching quality, and overall student satisfaction.

Key Features:

• Demographics: Age, gender, country, and optional province/state.
• Academic Info: University name, program level (Bachelor/Master/PhD), field of study, and year of study.
• Financials: Tuition fees (USD), scholarship status.
• Learning Modes: Online or on-campus classes.
• Student Experience: Campus facilities rating, teaching quality rating, and overall satisfaction.

*Use Cases: *

• Exploratory Data Analysis (EDA): Study global higher-education trends.
• Data Visualization: Generate plots, dashboards, and insights for student satisfaction and tuition.
• Predictive Modeling: Train machine learning models on student satisfaction, scholarship probability, or tuition prediction.
• Portfolio & Academic Projects: Perfect for Kaggle notebooks, reports, or machine learning practice.

Why Use This Dataset:

• Fully synthetic and privacy-safe—no real student data.
• Globally diverse, covering multiple countries and fields of study.
• Lightweight and ready for immediate analysis and modeling.
• Modular and expandable—easy to add more countries, programs, or features in future versions.

This dataset is ideal for beginners and intermediate data scientists seeking realistic, clean, and actionable educational data for analysis, modeling, and visualization projects.