M.S. in Data Science

Anyone interested in advancing their career or changing career paths by developing data science skills is encouraged to apply.

Successful applicants for both the M.S. in Data Science and Certification of Professional Achievement in Data Sciences programs should have:

• an undergraduate degree

a personal statement

• prior quantitative coursework (i.e., linear algebra, probability/statistics, etc.)
• prior introductory to computer programming coursework (i.e., Python, Java, C+, etc.)

We often have prospective students ask about how they should meet the required quantitative or computer programming prerequisites if they have not previously completed formal credit-bearing coursework. Many applicants often ask about completing massive open online courses (MOOC) as a means of meeting the prerequisites. While these strategies are encouraged, keep in mind that the admissions process is competitive. Faculty reviewers will often place more weight on formal coursework or work experience over MOOCs.  That said, MOOCs are routinely used to supplement learning and/or serve as a refresher course for many of our students.

Applicants are not required to have a degree in engineering; preparation in the field of data science is acceptable.

Since the M.S. in Data Science is a 30-credit degree program, most full-time students complete the program in three semesters (12 credits in the fall, 12 credits in the spring, and 6 credits in the fall). Students must complete the program in five years. Please note that international students must be enrolled on a full-time basis, which is at least 12 credits per semester.

The fall semester begins in early September. Please refer to the University’s academic calendar for exact dates: http://registrar.columbia.edu/event/academic-calendar

While many of our students have work experience, it is not required.

There are no minimum test score or GPA requirements to apply for admission consideration. Applicant scores and grades will be evaluated in the context of other applicants. 

Average Scores for the Fall 2019 cohort: 

• Average Undergraduate GPA: 3.76
• Average GRE:  168 (Q), 158 (V), 3.8 (W)
• Please note: For 2021, the GRE is optional

Please note that the admissions committee reviews applications from a holistic perspective. Applicants may offset lower test scores with captivating personal statements, strong letters of recommendation, etc. For more information regarding the standardized test requirements, please visit the Graduate Engineering FAQ page. 

M.S. in Data Science:  Yes, individuals that require an F-1 student visa may apply to this full-time degree program.

Certification of Professional Achievement: The Certification is a part-time, non-degree program. Individuals requiring an F-1 student visa sponsorship are not eligible to apply to this on-campus program, but would be eligible to apply to the online program.  For more information about the online Certification of Professional Achievement in Data Science program, please visit the CVN website.

Yes, students who have graduated from a three-year, degree-granting program are eligible to apply to the M.S. in Data Science program.

No, applicants may apply to only one program in Columbia Engineering at a time. If applicants apply to more than one program per term their applications may be invalidated.

Columbia does not allow students to be enrolled in more than one program at a time. We welcome applications from current Columbia students exploring the possibility of a transfer to our program. Columbia students may cross-register for data science courses, space permitting and with faculty/advisor approval; note that such students will not be eligible to receive a certification from the data science program.

Yes, you may apply again by submitting a new application and supplemental material. 

The review process is confidential and, therefore, we cannot offer additional information that is not in your letter.

For the on-campus programs, applications must be submitted via our online application system.

Please refer to the following links for more information:

• Columbia Engineering Application Process FAQ
• Columbia Engineering Standardized Test Scores FAQ
• Columbia Engineering Transcripts FAQ
• Office of Graduate Student Affairs

All applicants applying for the on-campus program must submit application materials via the online application. For the online program, applications must be submitted through Columbia Video Network (CVN). Once you register with a valid email address, you may log on as often as you need to fill everything out. Submit your application when complete.

First Priority: January 15th 2021

Second Priority: February 15th 2021

The following materials must accompany the online application for the M.S. in Data Science and Certification of Professional Achievement in Data Sciences:

• Official transcripts from every post-secondary institution attended
• Three (3) letters of recommendation
• Official Graduate Record Examination (GRE) General Test Scores*
• Personal Statement
• Curriculum Vitae / Résumé
• Non-refundable Application Fee
• International applicants may have to submit an English language test score for the M.S. application: TOEFL, IELTS or PTE test scores

*Certification applicants are not required to submit test scores, but are encouraged to do so.

Please note: For 2021, the GRE is optional

Please note: For 2021, the GRE is optional

No, the GRE requirement cannot be waived. An applicant who has completed a graduate degree is still required to submit a valid test score.

Columbia Engineering’s code is 2111; a department code is not required. SEAS Graduate Admissions cannot access GRE and TOEFL scores sent to another institution code, even if sent to another school at Columbia.  

For IELTS scores, enter your TRF number on the application for admission. Columbia Engineering’s admissions office downloads IELTS scores that have been transmitted to their e-download account. Please contact your test center and​ request that your scores be sent to ​the IELTS e-download account. You may select Columbia Engineering by searching for Columbia University under “List of Organizations subscribing to the E-TRF Query” and selecting “The Fu Foundation School.” GSA will not accept paper IELTS test report forms.

Please note: For 2021, the GRE is optional

For the on-campus program application, please email seasgradmit@columbia.edu. For the distance education (online) program application, please email admissions@cvn.columbia.edu. Other questions about the application process? Please visit the Graduate Engineering Admissions page.

Updated information regarding the Columbia School of Engineering and Applied Science tuition may be found on the Student Financial Services website.

Tuition: https://sfs.columbia.edu/tuition

Cost of Attendance by Program (including fees): https://sfs.columbia.edu/sfp-grad-engin

M.S. in Data Science: U.S. citizens and permanent residents applying to the M.S. program may be eligible for financial aid from the U.S. Department of Education. Please complete the FASFA form to find out if you qualify.

Certification of Professional Achievement: As a part-time, non-degree program, this program is currently not eligible for FAFSA funding.

Please review the Student Financial Planning page for more details: https://sfs.columbia.edu/sfp-grad-engin

Please visit the  Student Financial Planning Office website for information regarding funding options. We are unable to offer institutional aid to our students, but we do encourage all prospective students to seek funding from external sources, including scholarships offered by philanthropic or government organizations. Eligibility and application requirements will vary depending on the sponsor. Columbia University’s Find A Fellowship listing or the Columbia Engineering Fellowship List feature external scholarship opportunities. We also suggest that you consult with faculty, administrators, or mentors at your current or prior undergraduate school as they may also have knowledge of sources of funding. There are also a few interschool fellowships with very specific requirements available for varying amounts to students who qualify. To find out if you qualify for an interschool fellowship, please review the information on the Student Financial Services website for details. 

Columbia employees should speak with Human Resources regarding potential benefits.

Assistantships and work studies must be sought out by the student. You are welcome to look on Columbia’s Human Resources page for part-time, on-campus positions. Some are research-oriented; others are purely administrative. These are hourly positions and generally do not come with tuition benefits. The School of Engineering also posts research opportunities on the Student Research Program site. 

Most assistantships are typically posted closer to the beginning of each semester. Please note that most fully-funded positions are typically reserved for Ph.D. track students. Paid opportunities on-campus are typically hourly positions and do not come with tuition benefits. While these positions do not cover the cost of tuition, it can offset the cost of attendance. 

Additionally, DSI students have an opportunity for on-campus, part-time work through two DSI programs:

DSI Campus Connections Program: We are able to connect our students with Columbia faculty and staff that need students with data science skills. Some of the positions are paid, while others may have the option to be used for credit.

DSI Scholars Program:  This program engages Columbia’s undergraduate and master’s degree students in data science research with Columbia faculty, provides student researchers with unique enrichment activities, and aims to foster a learning and collaborative community in data science at Columbia. The opportunity includes a stipend. 

The M.S. in Data Science program requires 30 credits to be completed part-time (less than 12 credits per semester) or full-time (12 or more credits per semester). All degree requirements must be completed within five years of the beginning of graduate study.

The Certification of Professional Achievement program requires 12 credits (4 courses) to be completed part-time. Most students complete the program in one year (two courses in the fall, two courses in the spring), but can take two years to complete the program.

The M.S. in Data Science program is an on-campus program only. To accommodate working students, most of our core courses are offered in the evening. The Certification of Professional Achievement program in Data Sciences is offered both on-campus as well as online.

Data scientists need to be versatile and often code in multiple languages. Courses may require R, Python, shell scripts, C, and Java. If you are proficient in one language it will be easier to learn others. Students with a demonstrated quantitative background and no programming skills must gain proficiency in one language before registering for Algorithms for Data Science.

We do not offer a dual degree with the M.S. in Data Science at this time.

Our students follow Columbia’s Department of Computer Science’s curricular practical training (CPT) guidelines which allow one fieldwork credit per semester and a maximum of three credits. Please see http://www.cs.columbia.edu/education/ms/cpt for more information.

The M.S. in Data Science is a government-designated STEM degree and so international students may be eligible for the 24-month F1 optional practical training (OPT) extension.

More information on CPT and OPT is available through Columbia’s International Students and Scholars Office: http://www.columbia.edu/cu/isso/visa/F-1/F-1_PT_overview.html

No, Columbia Engineering’s policy prohibits the transfer of courses completed outside of Columbia University to be counted towards the minimum degree requirements. Students that have completed courses that potentially overlap with core requirements may seek advisor approval for a waiver and substitute said credits with additional electives.