Master of Science in Data Science

The Master of Science in Data Science allows students to apply data science techniques to their field of interest, building on four foundational courses offered in our Certification of Professional Achievement in Data Sciences program. Our students have the opportunity to conduct original research, included in a 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 seven centers.

ELIGIBILITY REQUIREMENTS

  • Undergraduate degree
  • Prior quantitative coursework (calculus, linear algebra, etc...)
  • Prior introductory to computer programming coursework

WHO SHOULD APPLY?

Individuals looking to strengthen their career prospects or make a career change by developing in-depth expertise in data science.

APPLICATION REQUIREMENTS

We routinely offer a number of online information sessions and other recruiting events, please [Click Here]. To learn more about the admissions application requirements and to submit your application, please visit the Office of Graduate Student Affairs

DEADLINE

Applications are currently accepted for fall admission only. (We do not have a spring admission cycle.)
The priority deadline for Fall 2016 application submission is February 15th.  [Apply Here]

TUITION AND FEES

Students enrolled in the Master of Science program pay Columbia Engineering's rate of tuition, $1,858 per credit for the 2016-2017 academic year. Tuition and fees are prescribed by statute and are subject to change at the discretion of the Trustees. For more information on rates of tuition and other applicable fees, refer to Student Financial Services and the Columbia Engineering Bulletin.

QUESTIONS

If you would like to learn more, please refer to our Frequently Asked Questions or sign up for one of our regularly scheduled online information sessions.

CURRICULUM

Candidates for the Master of Science in Data Science are required to complete a minimum of 30 credits, including 21 credits of required/core courses and 9 credits of electives. This program may be pursued part-time or full-time.

For the most up-to-date course offering and schedule information refer to COURSES.

REQUIRED/CORE COURSES:

STAT W4203 PROBABILITY THEORY

CSOR W4246 ALGORITHMS FOR DATA SCIENCE

STAT W5703 STATISTICAL INFERENCE AND MODELING

COMS W4121 COMPUTER SYSTEMS FOR DATA SCIENCE

COMS W4776 MACHINE LEARNING FOR DATA SCIENCE

STAT W4701 EXPLORATORY DATA ANALYSIS AND VISUALIZATION

ENGI E4800 DATA SCIENCE CAPSTONE AND ETHICS


ELECTIVES:

Nine (9) credits of elective courses should be drawn upon existing graduate level courses at Columbia University.  In addition to advisor approval, elective course selection will be subject to course prerequsities, course availability, and the cross-registration procedures of the school/department offering the requested courses.

COMS E6910x and y FIELDWORK
1 pt. Members of the faculty.
Prerequisites: Obtained internship and approval from Professor Eleni Drinea. Only for M.S. students in the Computer Science Department (and Data Science Institute) who need relevant work experience as part of their program of study. Final report required. This course may not be taken for pass/fail credit or audited. For more information visit http://www.cs.columbia.edu/education/ms/cpt.



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