Only at Cornell常春藤唯一：一年制速通数据科学项目

康奈尔大学（Cornell University）统计与数据科学系（Department of Statistical Science）开设的 MPS in Data Science and Applied Statistics（数据科学与应用统计硕士），是常春藤盟校中以应用为导向的数据科学项目之一。该项目学制1年，旨在培养具备统计建模、机器学习、大数据分析能力的跨学科人才，课程设计兼顾理论深度与行业实践需求。与康奈尔其他工程或计算机科学类项目不同的是，该专业更注重统计学基础与实际问题解决，适合希望在金融、医疗、科技、政府等领域从事数据分析工作的学生。相当于其他常春藤名校项目来说，学制较短，课程强度偏中等。录取背景多元化，选课的灵活度也相当高。根据康奈尔2024年就业报告及PayScale数据显示，本专业毕业生平均起薪：100,000（含奖金），金融领域量化分析师可达$120,000+（纽约、旧金山）。科技公司数据科学家可达$140,000（如Meta、Google）。

课程设置

康奈尔的Data Science and Applied Statistics 修读毕业需完成30个学分核心课程分为统计基础、机器学习、应用领域三大模块，详细的课程清单如下：

- STSCI 5030: Linear Models with Matrices (4 credits) Fall
- STSCI 5080: Probability Models and Inference (4 credits) Fall
- STSCI 5954: Project Development & Professional Communication (2 credits) Fall
- STSCI 5955: Real Time Project Management (1 credit) Spring
- STSCI 5999: Applied Statistics MPS Data Analysis Project (4 credits) Spring

Additional Required Courses for Data Science Track:
- STSCI 5045: Python Programming and its Applications in Statistics (4 credits) Fall
- STSCI 5060: Database Management and SAS High Performance Computing with DBMS (4 credits) Fall
- STSCI 5065: Big Data Management and Analysis (3 credits) Spring

Statistical Science Electives:
- STSCI 5010: Applied Statistical Computation with SAS (4 credits)
- STSCI 5040: R Programming for Data Science (4 credits)
- STSCI 5045: Python Programming and its Applications in Statistics (4 credits)
- STSCI 5050: Modern Regression Models for Data Science (4 credits)
- STSCI 5060: Database Management and SAS High Performance Computing with DBMS (4 credits)
- STSCI 5065: Big Data Management and Analysis (3 credits)
- STSCI 5090: Theory of Statistics (4 credits)
- STSCI 5100: Statistical Sampling (4 credits)
- STSCI 5111: Multivariate Analysis (4 credits)
- STSCI 5140: Applied Design (4 credits)
- STSCI 5160: Categorical Data (3 credits)
- STSCI 5520: Statistical Computing (4 credits)
- STSCI 5270: Introduction to Survival Analysis and Loss Models (3 credits)
- STSCI 5550: Applied Time Series Analysis (4 credits)
- STSCI 5600: Integrated Ethics in Data Science (2 credits)
- STSCI 5610: Data Science in Risk Modeling (2 credits)
- STSCI 5630: Operations Research Tools for Financial Engineering (4 credits)
- STSCI 5640: Statistics for Financial Engineering (4 credits)
- STSCI 5740: Data Mining and Machine Learning (4 credits), forbidden overlap with CS 5780, ORIE 5740 or ORIE 5741
- STSCI 5750: Understanding Machine Learning (4 credits)
- STSCI 5780: Bayesian Data Analysis: Principles and Practice (4 credits)
- STSCI 6520: Statistical Methods I (4 credits)
- STSCI 6780: Bayesian Statistics and Data Analysis (3 credits)

康奈尔的MPS in Data Science and Applied Statistics项目毕业生主要在金融行业,科技与互联网,医疗与公共健康政府与非营利组织等领域完成就业，凭借其统计学根基与跨领域应用的平衡，成为常春藤盟校中务实型数据科学教育的代表。对于具备数学与编程基础的申请者，该项目能为就业找工作提供扎实的技能与康奈尔全球校友网络的资源支持。