Normalized Relational Dataset of AI & Data Science University Programs (2020-2024)

This dataset contains a fully normalized relational database describing university level characteristics, AI/Data Science academic programs, admission requirements, and annual institutional statistics for the years 2020-2024. The goal of the dataset is to provide a clean, structured, and reproducible representation of higher education program information that can be used for analysis, querying, and relational modeling.

The dataset includes four tables: University, Program, AdmissionRequirements, and AnnualUniversityStats. Each table represents a distinct entity group and is structured according to relational database normalization principles. The University table contains static institutional attributes such as name, state, institution type, campus size, and website. The Program table contains program-level attributes including degree level, year first offered, focus area, and tuition. The AdmissionRequirements table stores minimum GPA, standardized test requirements, and minimum test scores for each program. The AnnualUniversityStats table contains year-specific institutional metrics such as national ranking, total student population, number of programs, and average tuition.

All data was collected from publicly available sources including IPEDS College Navigator, university factbooks, institutional research dashboards, US News Education, and official program websites. Because universities do not consistently publish program-level outcomes or historical data for every year, the dataset focuses on attributes that are reliably available across institutions.