Apply - Master in Data Science & Analytics

Welcome! We are excited that you are interested in applying to our program.

Our program provides rigorous, cutting-edge training to prepare you to be a leader in data science or apply to related Ph.D. programs. Our classes utilize knowledge of Multivariate Calculus (usually called Calc I and II or sometimes Calc III) and Probability and Statistics (which can be called Math Stats, Econometrics, Regression Analysis, etc.). Experience with computer programming (such as R, Python, C++, Java, etc). Linear Algebra, while not required, is also very helpful.

We love the diversity of experiences our students bring to the program. They come from a very broad and wide range of backgrounds, including economics, marketing, business, computer science, engineering, math, statistics, linguistics, public policy, and others. Accordingly, it is not uncommon for applicants to be missing one or more prerequisites. If you are missing any of the prerequisites, or if you want to be better prepared in R, Python, etc. (which is always a smart idea) we recommend that you fill in gaps via online, local community college, or other similar options.

Include any certificates that you acquire with your application. If you want to submit by the early deadline and have not yet completed a course (so do not yet have the certificate), list the courses you are taking on your application and email the certificates as soon as you have them to gradanalytics@georgetown.edu

Admissions Deadlines

Fall Priority: December 15
Applications submitted by this date will receive priority consideration for admission and scholarship aid.
Note: All supporting materials must also be received by December 15th for priority consideration.
Fall Final: January 15
Applications received by this date will be reviewed but with reduced priority.
Note: All supporting materials must also be received by January 15th for consideration.

Admission Materials

Prospective students should submit or arrange for the following items:

Online Application
Non-refundable Application Fee
Resume or CV
Statement of Purpose
Unofficial transcripts from all undergraduate and graduate institutions attended (International applicants who attended institutions outside the United States must use a transcript evaluation service.)
- Do not send electronic or paper copies of your transcripts before receiving an offer of admission. Review the unofficial transcript requirements for additional details and FAQs.
- International applicants who attended institutions outside of the United States must submit their transcripts in the form of a course-by-course evaluation using a credential evaluation service that is a member of the National Association of Credential Evaluation Services (NACES ), such as WES ICAP or SpanTran Course Analysis. (These evaluations are not a requirement of all programs in the Graduate School, but are required for the Data Science & Analytics Program. No exceptions will be made.)
- You will not need to send your transcript evaluation to our school at this time; instead, you should ask the evaluation service to send the evaluation directly to you, and then you should upload the evaluation directly to the online application. An official transcript will be required if you are offered admission to the program.
- Applicants may use other credential evaluation services that are members of the National Association of Credential Evaluation Services (NACES) but must still submit official transcripts from the institution to Georgetown if the evaluation does not include an official copy of the transcripts you had evaluated.
- The transcript evaluation process can be lengthy; therefore, we encourage applicants to begin this process well in advance of the application deadline to ensure timely receipt and review by the Office of Graduate Admissions.
Official Recommendations (2)
TOEFL/IELTS score, if applicable
- Applicants who have not attended an institution of higher education where the primary language of instruction is English and who are not native speakers are also required to demonstrate proficiency in the English language. Non-native speakers must achieve at least a minimum score on either the TOEFL or IELTS.
  - TOEFL: A minimum score of 100 on the Test of English as a Foreign Language (TOEFL).
  - IELTS: A minimum score of 7.5 from the International English Language Testing System (IELTS).
- Test scores should be received by the application deadline date. Applicants should allow six to eight weeks from the test date for the reporting of scores. If you are a non-native speaker of English and received a bachelor’s or advanced degree from an accredited institution of higher education where English is the primary language of instruction, you do not have to submit TOEFL or IELTS scores.
- Georgetown University’s institution code for reporting TOEFL scores is 5244.
The GRE is not required.

Admission Requirements

As an applicant, you should have completed the following college-level courses:

Required: Multivariable Calculus (3 credits)
Required: Calculus-based Statistics (3 credits)
Required: Computer Programming (3 credits, major language)
Preferred: Linear Algebra (3 credits)
Preferred: Data Structures (3 credits)
Preferred: Algorithm Analysis and Design (3 credits)

The program utilizes R and Python extensively, and applicants are expected to be proficient with these languages prior to enrollment. You may demonstrate your programming knowledge through courses completed, certificates earned, or other evidence of systematic training together with suitable work experience.

GPA

A minimum undergraduate GPA of 3.0 (on a 4.0 scale) is required. Alternative combinations of coursework and/or experience can be used to support an application and will be considered on a case-by-case basis.

Resources for Completing Prerequisites

While we don’t endorse any specific online program, the following courses align with our program’s learning objectives:

How To Apply

Admissions Deadlines

Admission Materials

Admission Requirements

GPA

Resources for Completing Prerequisites

R Courses

Python Courses

Calculus, Linear, and Math for Data Science and ML

Other Math Options

Probability and Statistics-Multiple Options Based on Prior Knowledge

Reference