Three eligibility requirements
An undergraduate degree, prior quantitative coursework such as calculus and linear algebra, and prior introductory programming skills in languages such as Python, SQL or R.
Master's · Columbia University
Columbia Data Science MS: prerequisites first, then two fall deadlines
Columbia's MS in Data Science is run by the Data Science Institute with the Department of Statistics and Columbia Engineering's computer science and industrial engineering and operations research departments. The programme page lists three eligibility requirements: an undergraduate degree, prior quantitative coursework and prior introductory programming skills. It lists fall deadlines of 15 January (priority) and 15 February, and marks the GRE as optional for the 2026 applications.
Official information · fall deadlines of 15 January and 15 February
What Columbia asks for in Columbia Data Science MS
Taken from the Columbia Data Science Institute MS in Data Science page and the Columbia Engineering application-requirements page, read on 3 November 2026. The pages list fall deadlines of 15 January and 15 February and do not state the entry year in a labelled field; confirm the entry term and every date on the pages before you rely on it.
For career strengthening or a career change
The page describes the programme as being for people looking to strengthen their career prospects or make a career change by developing expertise in data science.
GRE optional for the 2026 applications
GRE General Test scores are optional for the 2026 applications. TOEFL, IELTS or PTE Academic scores are required if applicable.
Statement, CV, three letters and transcripts
The application includes an online application, a personal statement, transcripts from every post-secondary institution attended, three recommendation letters and a curriculum vitae or résumé. An interview may be requested.
Two fall deadlines
The programme page lists a fall priority deadline of 15 January and a final deadline of 15 February. Deferrals are not offered.
21 core credits and a capstone
The degree requires 21 credits of core coursework and a minimum of nine elective credits, and ends in a semester-long, mentored capstone project.
Official sources
- Columbia Data Science Institute: MS in Data Sciencedatascience.columbia.edu
- Columbia Engineering: Graduate Application Requirementsengineering.columbia.edu
Read on 3 November 2026 on the Columbia Data Science Institute MS in Data Science page and the Columbia Engineering application-requirements page. The course descriptions, the capstone detail, the elective tracks and the tuition pages were not read and are not stated.
Fit
Prerequisites are the eligibility test
The page states eligibility as three requirements rather than a grade or score. The readings below mix Columbia's wording with Avandy's judgment, and the labels say which is which.
Quantitative coursework
The page names calculus and linear algebra as examples and does not give a grade or course list.
Programming skills
The page asks for prior introductory computer programming skills, with Python, SQL and R as examples, and does not name a course or a level.
Avandy's judgment (heuristic, not a university rule)
Because the page names no grades, the evidence you can show is the coursework and projects themselves. If either area is thin, address it in your application before the deadline rather than after.
Decision
A data science degree, not a computer science one
Columbia also offers a Computer Science MS, and the two are separate programmes with separate pages.
Structure
The Data Science MS has 21 core credits and at least nine elective credits, ending in a mentored capstone, with core courses in algorithms, statistical inference, machine learning, data analysis and scalable data systems.
Waivers
Students with prior preparation may waive or test out of some core courses, reviewed individually, which lets them take more electives.
Avandy's judgment (heuristic, not a university rule)
Choose between this and a computer science master's by what you want to build. A data science degree leans toward statistics and applied analysis, while the department's own page describes the computer science degree around pathways.
Application
The written application and the optional test
With the GRE marked optional for 2026, the written parts carry the application.
Materials
A personal statement, transcripts, three recommendation letters and a CV. The page lists an interview as possible on the engineering page.
The test position
Both pages mark the GRE as optional for 2026. Check them for the cycle you are applying to, because the label is specific to 2026.
Avandy's judgment (heuristic, not a university rule)
Optional does not mean ignored. Decide whether a score adds evidence your coursework does not, and leave it out if it does not.
Planning
Planning for the January and February deadlines
The pages list fall deadlines of 15 January and 15 February and do not state the entry year in a labelled field, so check the entry term on the pages.
What to do now
Check your quantitative and programming evidence, brief three recommenders and draft the statement. Re-read the pages before submitting, because the school can change them.
Support
Independent support with course choice and the written application
Avandy provides independent academic and admissions support. It is not affiliated with Columbia University or any of its departments. Support sits within the Avandy Trinity Advisory Model: a Strategic Admissions Consultant, a PhD-level Academic Mentor and a Subject-specific Tutor, working to the published requirements of each course. No outcome is promised.
Questions
Questions applicants ask
Is the GRE required for the Columbia Data Science MS?
The pages mark GRE General Test scores as optional for the 2026 applications. Check the pages for your cycle.
What are the fall application deadlines?
The programme page lists 15 January as the priority deadline and 15 February as the final deadline.
What prerequisites does the programme list?
An undergraduate degree, prior quantitative coursework such as calculus and linear algebra, and prior introductory programming skills such as Python, SQL or R.
How many credits is the degree?
The page says 21 credits of core coursework and a minimum of nine elective credits, ending in a capstone project.
Can I defer my place?
No. The Columbia Engineering page says deferrals will not be offered and that you should apply for the term you intend to enrol in.
Students and families
Talk to us about the Columbia Data Science MS
Tell us about your degree, your grades, your relevant experience and the master's courses you are weighing. A senior adviser will review the academic profile before recommending how to prepare the application.