The MS in Data Science (MSDS) in Computing & Data Sciences at Boston University prepares you to make significant contributions to all aspects of computational and data-driven processes that are woven into all aspects of society, economy, and public discourse. It is our goal that this program leads to solution of problems and synthesis of knowledge related to the methodical, generalizable, and scalable extraction of insights from data as well as the design of new information systems and products that enable actionable use of those insights to advance scholarly as well as practical pursuits in a wide range of application domains.
The MSDS is a flexible program designed to meet the goals of students looking to pursue either academic or professional careers in Data Science. Upon completion of the program, students will be prepared to pursue careers in which they will become leaders in their chosen areas, whether in academia through advanced graduate work in a PhD, or in industry (by collaborating, directing, and effectively managing diverse teams of practitioners working at the forefront of industrial R&D).
The MSDS in Computing and Data Sciences is currently designated by US Department of Homeland Security (DHS) as a STEM-eligible degree program. International students in F-1 student status may be able to apply for a 24-month extension of their 12-month Optional Practical Training (OPT) employment authorization. More information about STEM OPT eligibility is available from the BU International Students and Scholars Office (ISSO).
The MSDS is a 32-credit flexible program designed to meet the goals of students looking to pursue either academic or professional careers in data science, and can be completed in as little as 9 months. Students will declare either a Core Methods Focused Concentration or Applied Methods Focused Concentration. In addition to the core curriculum and concentration courses, the MSDS program offers students a unique opportunity to enhance their learning through an optional summer internship or master’s thesis course. As a result, the program can be extended and completed over 12 or 16 months. All students begin the program once every year in September; Spring entry term is not offered.
Eight semester courses (32 credits) approved for graduate study are required.
Course requirements include 5 competency courses, with at least one in each of the following areas:
A1 Modeling and Predictive Analytics
A2 Data-Centric Computing
A3 Machine Learning and AI
A4 Social Impact
A5 Security and Privacy
All MSDS students must declare either a core methods concentration or an applied methods concentration, both of which consist of 3 courses (12 credits)
Core Methods Option
Methods focused students are expected to be interested primarily in the development of general (application agnostic) data science methods and will most likely come from STEM undergraduate majors.
Students will take DS 701 and 2 additional courses from any of the A1, A2, or A3 competencies.
Applied Methods Option
Applied Methods focused students are expected to be especially interested in the development and application of special-purpose data science in applied areas such as Management, Public Health, Cybersecurity, etc. Such students may also be transitioning into data science from one of those fields.
Students will take DS 701 and 2 additional courses from any of the approved applied methods courses.
Mastery of the principal tools of data decision making, including defining models, learning model parameters, management, and analysis of massive datasets, and making predictions.
Demonstrated competence in application of data science tools to address substantive questions in one or more applied areas, and will address those questions through sophisticated use of data science tools, including tools specifically appropriate for each applied area.
Ability to extend tools of data decision making, including building specialized computational pipelines, automating data workflows, and developing human-computer interfaces.
Ability to interpret and explain results, including assessing uncertainty and developing data visualizations.
Gain awareness of the social impacts of data centered methods, including ethical considerations, fairness, and bias.
Ability to understand and adhere to policy, privacy, security, and ethical norms.
Applicants are expected to have earned a bachelor’s or master’s degree in one of the methodological or applied disciplines relating to the computational and data-driven areas of scholarship in Data Science. For example, applicants with degrees in one of the core areas of DS, namely, Computer Science, Electrical & Computer Engineering, and Mathematics & Statistics, or equivalent. Applicants with degrees in applied areas of DS (such as information systems, economics, bioinformatics, physics, astronomy, earth & environment, emerging media, among others should ensure that they meet the prerequisite requirements listed below.
Prerequisites are essential in preparing MSDS students for academic success. We Expect prospective applicants to have completed courses equivalent to the list below prior to entering the program.
- Introductory Programming course (eg, Python, Java, C++, R) equivalent to CAS CS 111
- Second course in Programming, equivalent to CAS CS 112 (Data Structures)
- Introductory Discrete Mathematics
- Linear Algebra
- Introductory Statistics and Probability
- Calculus, to the level of Calculus BC Advanced Placement
- Introduction to Algorithms
To accommodate a diversity of backgrounds and preparations of prospective students, a holistic admission review process will be utilized and as such, GRE tests and scores are not required, but could be optionally provided and considered as part of the applicant’s portfolio, which could also include evidence of prior, relevant preparation, including creative works, code repositories, etc.
If your first language is not English, you must take the Test of English as a Foreign Language (TOEFL), International English Language Testing System (IELTS), or the Duolingo English Test (DET). International students who have completed a degree in the United States or at any English-speaking university do not need to submit any language proficiency scores.
Official scores can be emailed to firstname.lastname@example.org or mailed to:
Faculty of Computing and Data Science
665 Commonwealth Avenue
Boston, MA 02215
MINIMUM TOEFL SCORE - 90
We require a minimum score of 90 on the TOEFL. We must receive an official TOEFL score by the application deadline, and we recommend taking your TOEFL at least 20 days prior to our deadline. (Note: Our TOEFL code is 3087).
MINIMUM IELTS SCORE - 7.0
We require a minimum score of 7.0 on the IELTS with a minimum of 6.5 across all bands for your application to be reviewed. We must receive an official IELTS score by the application deadline, and we recommend taking your IELTS at least 20 days prior to our deadline. The application will ask for your Test Report Form Number (TRF).
DUOLINGO ENGLISH TEST SCORE 130
BU accepts results for the Duolingo English Test (DET) as evidence of English proficiency, which combines an English proficiency test with a brief video interview. Please submit your scores through the Duolingo Dashboard by selecting “Boston University School of Hospitality Administration” as your institution of choice. Students who are most competitive for admission will have a score of at least 130
Learn more about our English proficiency requirements here.
Official Transcripts from institutions in which you received undergraduate and/or graduate degrees*
Two Letters of Recommendation
Proof of English Proficiency(TOEFL, IELTS, etc.)*
As part of our commitment to a holistic review approach, submitting GRE scores is not required.
These requirements are covered in greater detail within the online application. *Unofficial transcripts may be submitted in lieu of official transcripts for the purpose of your application; official transcripts must be provided to BU in the event you are admitted to the program. **Applicants who received their degree(s) from an institution(s) in which the primary instruction was English are exempt from this requirement.
Final Application Deadline: May 1st
Contact the Admissions Team: email@example.com