All coursework offered at Columbia Graduate Center. Most courses are hybrid. This will mean that some weeks will substitute synchronous in classroom learning for asynchronous out-of-classroom learning.
The program consists of 10 courses. The requirements include:
- Four core courses in business, statistics, and computer science.
- Two statistics courses;
- Two computer science courses;
- An elective from statistics, computer science, or business; and
- A technical capstone project.
For the required statistics and computer science courses, one course is proscribed while the other is an elective.
For course descriptions, please see the Graduate Catalog.
CS703 Programming for Data Science (taught by CS faculty)
ST710 Statistical Computing (taught by Statistics faculty)
DS730 Business Analytics and Strategic Decision Making (taught by IS faculty)
DS851 Business Intelligence and Data Mining (taught by IS faculty)
Additional Required Courses
CS737 Machine Learning
ST765 Linear Statistical Models
DS795/796 Data Science Project
Computer Science Elective Courses
CS745 Multimedia data analysis and mining
CS746 Data Visualization
CS750 Special Topics in Computer Science
CS751 Independent Study
CS765 Database Retrieval
CS766 Information Retrieval and Natural Language Processing
Statistics Elective Courses
ST767 Multivariate Analysis
ST775 Generalized Linear Models and Multilevel Models
ST776 Bayesian Inference
ST778 Time Series
ST791 Special Topics in Statistics
ST792 Independent Study
Business Elective Courses
GB700 Ethics and Social Responsibility
GB701 Operations Management and Process Strategies
GB705 Leadership and Management
GB732 Data Management and Governance
GB733 Enterprise Systems
GB736 Data Visualization for Decision Making
GB852 Advanced Analytics
GB853 Social Media and Web Mining
GB735 Project Management