Structured Data on AI & Data Science Degree Programs from 20 Universities Across Five U.S. States

This dataset is a normalized collection of information about Artificial Intelligence (AI) and Data Science (DS) programs offered by universities in the United States. It includes data from 21 universities across multiple states, covering both public and private institutions, collected from the Integrated Postsecondary Education Data System (IPEDS) 2023 data cycle.
The 21 universities were selected based on their explicit listing of a Data Science major in IPEDS. Some recently established programs were not captured as they had not yet been recorded in the 2023 cycle. Well-known institutions such as Harvard and MIT also do not appear, not because they lack data science programs, but because they classify them under different department names or CIP codes, placing them outside the direct Data Science major search criteria.
The dataset is organized into four main tables: University, Degree, Admission, and Graduation_Rate. The University table contains general information such as school name, location, and institution type. The Degree table covers program details including CIP description, credits, and credential level. The Admission table includes application and enrollment data, SAT score ranges, and in-state and out-of-state tuition. The Graduation_Rate table tracks student outcomes by cohort, including overall and gender-based graduation rates. One institution is an all-women school, so its male graduation rate is recorded as not applicable rather than missing.
The database is designed using normalization up to Third Normal Form to reduce redundancy and maintain consistency. Each table is linked through keys, making it easy to query and analyze. This dataset can be used to compare universities, explore trends in AI and Data Science education, and better understand differences in admissions, cost, and student outcomes across institutions.

本数据集为经规范化处理的美国高校人工智能（Artificial Intelligence，AI）与数据科学（Data Science，DS）专业项目信息合集。数据覆盖全美多个州的21所院校，涵盖公立与私立两类办学主体，采集自全美高等教育集成数据系统（Integrated Postsecondary Education Data System，IPEDS）2023年度数据周期。

本次选取的21所高校，均在IPEDS中明确标注开设数据科学专业。部分新近设立的专业项目因尚未录入2023年度数据周期，未被纳入本数据集。诸如哈佛大学、麻省理工学院等知名高校未被纳入，并非因其未开设数据科学专业，而是该校将该专业归属于其他院系名称或教学项目分类码（Classification of Instructional Programs，CIP）下，超出了本次直接检索数据科学专业的筛选范围。

本数据集共设四张核心数据表：University、Degree、Admission与Graduation_Rate。其中，University表存储院校基础信息，包括校名、办学地点与院校类型；Degree表涵盖项目细节信息，包括CIP描述、学分要求与学位等级；Admission表包含申请与入学数据、学术能力评估测试（Scholastic Assessment Test，SAT）分数区间以及本州与外州学费标准；Graduation_Rate表按学生批次追踪学生培养成果，包括整体毕业率与分性别毕业率。其中一所院校为女子学院，因此其男性毕业率字段标记为“不适用”而非空值。

本数据库采用第三范式（Third Normal Form，3NF）进行规范化设计，以减少数据冗余并保障数据一致性。各数据表通过键值建立关联，便于开展查询与分析工作。本数据集可用于高校间对比、探究人工智能与数据科学教育的发展趋势，以及深入理解不同院校在招生政策、培养成本与学生培养成果方面的差异。