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AI and Data Science Academic Programs in the United States

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NIAID Data Ecosystem2026-05-10 收录
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https://data.mendeley.com/datasets/nkf7h4rtcc
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This dataset was created to organize and analyze information about Artificial Intelligence (AI) and Data Science (DS) academic programs offered by universities in the United States. The goal was to build a structured database that shows not only general university information, but also how programs, admissions, and outcomes are connected. The dataset includes five main tables: University, UniversityYearStats, DegreeProgram, AdmissionRequirement, and ProgramOutcomeStats. The University table contains basic details such as the school name, location, whether it is public or private, and student population. The UniversityYearStats table was created to track changes over a five-year period (2021–2025), including tuition, rankings, and program growth. The DegreeProgram table focuses on specific AI and Data Science programs, including degree level, focus area, duration, and tuition. AdmissionRequirement includes common requirements such as GPA, GRE, and TOEFL, while ProgramOutcomeStats provides general outcome information like enrollment, graduation rate, employment rate, and average salary. To build this dataset, I used publicly available information from the U.S. Department of Education College Scorecard and official university websites. Since there is no single dataset that contains all program-level details, some information was gathered manually and organized into a consistent format. All data was cleaned and structured in Excel before being imported into MySQL Workbench. The dataset was designed using relational database principles and normalized to Third Normal Form (3NF), which helps reduce redundancy and keep the data organized. Each table represents a specific type of information and is connected through primary and foreign keys. This makes it easier to run queries, analyze relationships, and expand the dataset in the future. Overall, this dataset can be used for learning database design, practicing SQL queries, or exploring trends in AI and Data Science education across U.S. universities.
创建时间:
2026-04-15
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