Program Overview

Program Overview

The Data Science Institute at Columbia University offers a Master of Science in Data Science (MSDS) program that provides students with a comprehensive education in data science. The program is designed to equip students with the theoretical foundations and practical skills necessary to succeed in the field of data science.

Curriculum

The MSDS program consists of 21 credits of core courses and a minimum of 9 credits of electives. The core courses provide a foundation in algorithms, statistics, data analysis, and machine learning. The electives allow students to explore specialized topics and interdisciplinary applications across the university.

Program Structure

• Students complete 21 credits of core courses and a minimum of 9 credits of electives.
• The program includes a capstone project that serves as the culminating academic experience.
• The capstone project allows students to apply data science methods to address complex, real-world problems.

Core Courses

• Provide a foundation in algorithms, statistics, data analysis, and machine learning.
• Include courses such as:
  • COMS W4121: Computer Systems for Data Science
  • COMS W4721: Machine Learning for Data Science
  • CSOR W4246: Algorithms for Data Science
  • STAT GR5701: Probability and Statistics for Data Science
  • STAT GR5702: Exploratory Data Analysis and Visualization
  • STAT GR5703: Statistical Inference and Modeling

Electives

• Allow students to explore specialized topics and interdisciplinary applications across the university.
• Include courses such as:
  • IEOR 4572: Data Science Applications in Insurance and Banking
  • IEOR 4573: Business Applications of Large Language Models (LLMs)
  • COMS 4705: Natural Learning Processing
  • COMS 6998: High Performance Machine Learning
  • COMS E6998: Natural Language Processing: Computational Models of Social Meaning
  • 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: Elements of Data Science
  • IEOR E4721: Topics in Quantitative Finance: Big Data in Finance
  • STATS GR5293: Topics in Modern Statistics: Applied Machine Learning for Financial Modeling and Forecasting
  • STAT 5293: Machine Learning for Computer Vision
  • STAT 5293: Design & Analysis of Online Experiments
  • STATS GR5293: Topics in Modern Statistics: Applied Machine Learning for Image Analysis

Research Areas

The Data Science Institute at Columbia University has several research centers and working groups that focus on various areas of data science, including:

• Smart Cities
• Sense, Collect, and Move Data
• Health Analytics
• Foundations of Data Science
• Financial and Business Analytics
• Data, Media, and Society
• Cybersecurity
• AI for Sciences and Engineering
• Education
• Computational Social Science

Engagement Opportunities

The Data Science Institute at Columbia University provides various opportunities for engagement, including:

• For Alumni
• For Faculty and Researchers
• For Industry
• For Students
• Giving