M.S. in Data Science

The m. S. In data science allows students to apply data science techniques to their field of interest. Ours is one of the most highly-rated and sought-after advanced data science programs in the world. 

Program Highlights

• Columbia data science students have the opportunity to conduct original research, produce a capstone project, and interact with our industry partners and world-class faculty.
• This program is jointly offered in collaboration with the Graduate School of Arts and Sciences’ Department of Statistics, and The Fu Foundation School of Engineering and Applied Science’s Department of Computer Science and Department of Industrial Engineering and Operations Research.

Where are Columbia data science graduates now?

• Alibaba, Amazon, Aptly Technology, Bilibili, ByteDance, BCG Gamma, C3 AI, China Telecom Americas, CIBC, Citibank, Cowen, CTA NYC, CURO Management, DIA Associates, DiDi, Discover Financial Services, Egan-Jones, Eightfold AI, Ernst & Young, General Electric, Goldman Sachs, Google, Hello Fresh, Houlihan Lokey, Huawei, IBM, Jingdong, J.P. Morgan, LinkedIn, McKinsey & Company, Meituan, Meta, MetLife, Microsoft, Moody’s, Nanjing Securities, NBC Universal, Netease Game, Nielson, Nuveen, Oscar Health, Oracle, PayPal, Prudential, Quaft Technologies, Resilience Code, Roku, SentiLink, Sentry, Sia Partners, Slalom Consulting, SparkCognition, Splunk, Starbucks, Tableau, Tata, Tencent, Vanguard, Visa, Walmart, Warner Music Group, WeRide Corp.

Curriculum
Computer Science

• COMS W4121 Computer Systems for Data Science- Spring Semester: 3 credits
• COMS W4721 Machine Learning for Data Science- Spring Semester: 3 credits
• CSOR W4246 Algorithms for Data Science- Fall Semester: 3 credits

Engineering

• ENGI E4800 Data Science Capstone and Ethics

Statistics

• STAT GR5701 Probability and Statistics for Data Science- Fall Semester: 3 credits
• STAT GR5702 Exploratory Data Analysis and Visualization- Fall Semester: 3 credits
• STAT GR5703 Statistical Inference and Modeling- Fall and Spring: 3 credits

Electives
About Electives

• COMS W4995 Topics in Computer Science: Applied Machine Learning
• COMS W4995 Topics in Computer Science: Applied Deep Learning
• COMS W4995 Topics in Computer Science: Causal Inference for Data Science
• COMS W4995 Topics in Computer Science: Data Analytics Pipeline
• COMS W4995 Topics in Computer Science: Elements of Data Science
• COMS E6998 Topics in Computer Science: Machine Learning with Probabilistic Programming
• COMS E6998 Natural Language Processing: Computational Models of Social Meaning
• EECS E6894 Topics in Information Processing: Deep Learning for Computer Vision, Speech, and Language
• IEOR E4571 Topics in Operations Research: Personalization Theory & Application
• IEOR E4721 Topics in Quantitative Finance: Big Data in Finance
• STATS GR5293 Topics in Modern Statistics: Applied Machine Learning for Financial Modeling and Forecasting
• STATS GR5293 Topics in Modern Statistics: Applied Machine Learning for Image Analysis

Cross-Registration

• Instructions for Non-Data Science Students