The MS in Data Science allows students to apply data science techniques to their field of interest.
Columbia data science students have the opportunity to conduct original research, complete 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 Columbia Engineering’s Department of Computer Science and Department of Industrial Engineering and Operations Research.
Innovative and Cutting-Edge Curriculum
Designed with both theoretical foundations and practical applications, our data science courses reflect the latest trends and technologies in data science such as machine learning, natural language processing, applied deep learning, and many more courses at the frontiers of data science taught by world-class Columbia faculty.
Program Structure
The M.S. in Data Science requires students to complete 21 credits of core coursework and a minimum of 9 elective credits, providing both depth and breadth across key data science disciplines.
Capstone Project
The Capstone serves as the culminating academic experience of the program. In this semester-long, mentored project, students apply data science methods to solve complex, real-world problems in collaboration with faculty or industry partners.
Program Overview
Eligibility
The MS in Data Science is for individuals looking to strengthen their career prospects or make a career change by developing expertise in data science.
Our students have the opportunity to conduct original research, including through the Capstone project, and interact with our industry partners and faculty. Students may also choose an elective track focused on entrepreneurship or a subject area covered by one of our eight centers.
Eligibility Requirements
- Undergraduate degree
- Prior quantitative coursework (calculus, linear algebra, etc.)
- Prior introductory computer programming skills: Python, SQL, R, etc.
Deadlines
Fall Application Deadline
- Priority Deadline: January 15
- Final Deadline: February 15
Application Process
Application Requirements
- Online application
- Personal Statement
- Uploaded transcripts from every post-secondary institution attended
- Three recommendation letters
- Curriculum vitae / resumé
- Official Graduate Record Examination (GRE) General Test Scores are optional for the 2026 applications
- $85 non-refundable application fee
- TOEFL, IELTS or PTE Academic test scores, if applicable
Curriculum
Core Courses
Core courses build a strong foundation in algorithms, statistical inference, machine learning, data analysis, and scalable data systems.
Please Note: Students with prior academic preparation in specific core areas may be eligible to waive or test out of certain core courses, allowing them to take additional electives. Waivers are reviewed individually, based on previous coursework and instructor approval.
Electives
Electives allow students to explore advanced or specialized topics and pursue interdisciplinary interests across the university. In addition to Data Science Institute (DSI) courses, students are encouraged to take approved electives in departments such as Computer Science, Statistics, Engineering, Business, Public Health, Economics, and more.
Academic advisors work closely with students prior to registration to determine course relevance, eligibility, and fit (4000-level or above; letter-graded).
Computer Science
MS Data Science Recent Program Overview
Information sessions are offered throughout the year to provide an overview of the program and guidance on the application process. A recorded session is available for prospective students who cannot attend.