AI and Data Science Academic Programs in U.S. Universities (Normalized Relational Dataset)

This dataset contains organized information about universities in the United States that offer programs in Artificial Intelligence and Data Science. I created it as part of my DATA 6200 Data Management course to support database design, analysis, and research on academic programs in these fields. All of the information in the dataset comes from publicly available sources. These include NCES College Navigator (https://nces.ed.gov/collegenavigator/ (nces.ed.gov in Bing)), U.S. News Best Colleges (https://www.usnews.com/best-colleges (usnews.com in Bing)), DataScienceGraduatePrograms.com (https://www.datasciencegraduateprograms.com/), individual university program pages, GradSchools.com (https://www.gradschools.com/), NCES IPEDS (https://nces.ed.gov/ipeds/), and university faculty directories. These sources provide reliable details about universities, degree programs, admissions requirements, and yearly institutional statistics.

The dataset is structured into five tables: University, DegreeProgram, AdmissionRequirements, YearlyUniversityStats, and Faculty. Each table represents a different part of the overall topic. The University table includes basic institutional information such as state, type, enrollment, and website. The DegreeProgram table lists program names, degree levels, tuition, and duration. AdmissionRequirements includes minimum GPA, test requirements, deadlines, and notes. YearlyUniversityStats contains time‑based data such as tuition, enrollment, and national rankings for multiple years. The Faculty table includes faculty names, departments, research areas, and email addresses.

The goal of this dataset is to provide a clean, normalized structure that can be used for academic analysis, database modeling, or research on trends in AI and Data Science education. Because the data is organized in Third Normal Form, it can be easily imported into a relational database and used for queries, visualizations, or further study. This dataset is intended for educational and research purposes.

本数据集收录了美国开设人工智能与数据科学相关专业的高等院校的结构化信息。本数据集由作者在DATA 6200数据管理课程中创建，用于支撑该领域学术项目的数据库设计、分析与研究工作。数据集内所有信息均来自公开可获取的数据源，包括国家教育统计中心高校导航系统（NCES College Navigator，https://nces.ed.gov/collegenavigator/，即必应搜索中的nces.ed.gov站点）、《美国新闻与世界报道》最佳大学榜单（U.S. News Best Colleges，https://www.usnews.com/best-colleges，即必应搜索中的usnews.com站点）、DataScienceGraduatePrograms.com（https://www.datasciencegraduateprograms.com/）、各高校官方项目页面、GradSchools.com（https://www.gradschools.com/）、国家教育统计中心综合高等教育数据系统（NCES IPEDS，https://nces.ed.gov/ipeds/）以及高校教职工名录。上述数据源可提供关于高校、学位项目、招生要求及年度院校统计数据的可靠细节。

本数据集共包含五张规范化数据表：高校表（University）、学位项目表（DegreeProgram）、招生要求表（AdmissionRequirements）、年度高校统计表（YearlyUniversityStats）以及教职工表（Faculty），每张表对应主题的不同维度。其中，高校表收录院校基本信息，如所在州、院校类型、在校生规模与官方网站；学位项目表列出项目名称、学位层级、学费与学制；招生要求表涵盖最低GPA要求、考试要求、申请截止日期及补充说明；年度高校统计表包含多维度时序数据，如学费、在校生人数与历年全国排名；教职工表则收录教职工姓名、所属院系、研究方向与电子邮箱地址。

本数据集旨在提供一套清晰规范的结构化框架，可用于人工智能与数据科学教育领域的学术分析、数据库建模或相关趋势研究。由于该数据集采用第三范式（Third Normal Form）进行规范化组织，可轻松导入关系型数据库，用于查询、可视化或后续拓展研究。本数据集仅用于教育与科研用途。