Frequently Asked Questions
This Frequently Asked Questions (FAQ) page answers many questions about applying to UBC Master of Data Science Program. Please read carefully to see if your question has been answered here before contacting the Master of Data Science offices. Do not hesitate to contact us if your question has not been answered below.
What are the main differences between the MDS programs at the Vancouver campus and Okanagan campus?
The programs were both designed by computer science and statistics experts, with input from local industry to give students the skills they need to succeed in a data science career. The curricula are very similar, with only minor variances in focus. The program at the Okanagan has a stronger emphasis on optimization and statistics, while the program at the Vancouver campus is designed to give students a broader skillset. The more significant differences are related to cohort size and specific industry partners.
The Okanagan campus offers an intimate learning environment and tight-knit MDS cohort, which is limited to 40, leaving students with a strong network of peers. Industry partners are varied, but the campus is located in an area known for its more than 2,000 tech start-ups, and often referred to as the “Silicon Valley of the North.”
The Vancouver campus offers an engaging, culturally enriched university experience on a 400-hectare campus, with a diverse cohort of up to 100 students. Its location in Vancouver provides strong connections with a wide variety of industry partners, resulting in diverse networking/career options.
Can I transfer from the Vancouver campus to the Okanagan campus or vice versa?
No, at this point, you cannot transfer between programs.
If I have taken similar courses in my previous degree can I get transfer credits?
No, the MDS program is a cohort based program. All our courses are developed specifically for the program and build on each other. As such all students start the program together, take the same courses in the same order and graduate as a cohort.
What does the Okanagan cohort look like? Is it different from Vancouver?
Both campuses attract bright minds from a wide range of backgrounds. In both cases, there is a mix of domestic and international students, a variety of educational backgrounds and a range of professional experience. Specifically, the 2018/19 Okanagan cohort is:
- 50% male; 50% female
- 22 – 48 years of age
- from: Canada, India, China, Iran, Malaysia, Nigeria, Uganda, Venezuela
- has professional experience ranging from none to advanced careers
- have past educational experience in: engineering, finance, computer science and engineering, math, statistics, microbiology, human kinetics and psychology
When will the MDS - Computational Linguistics specialization be available?
The program has recently been approved by the British Columbia Ministry of Advanced Education and we will begin to accept applications for September 2019 sometime in mid-March. Subscribe for program news and updates on when applications will open.
What is the difference between MDS and MDS – Computational Linguistics specialization?
Offered at the Vancouver campus, the Computational Linguistic specialization is a degree tailored to those with a passion for language and data. Over 10 months, the program combines foundational data science courses with advanced computational linguistics courses—equipping graduates with the skills to turn language-related data into knowledge and to build AI that can interpret human language.
Can I apply to the MDS program at both the Vancouver and Okanagan campuses as well as the Computational Linguistic specialization?
- Yes. You can apply for more than one of the UBC Master of Data Science programs, but you will be required to complete and submit a separate application for each program (and pay separate application fees).
Do the pre-requisite courses have to be taken at UBC?
- No. The pre-requisite courses can be taken at any accredited university. Below are short descriptions of the UBC courses eligible as MDS pre-requisite courses. Courses taken at other institutions should match in topic and content.
- CPSC 110 (4) Computation, Programs, and Programming: Fundamental program and computation structures. Introductory programming skills. Computation as a tool for information processing, simulation and modeling, and interacting with the world
- APSC 160 (3) Introduction to Computation in Engineering Design: Analysis and simulation, laboratory data acquisition and processing, measurement interfaces, engineering tools, computer systems organization, programming languages.
- CPSC 103 Introduction to Systematic Program Design: Computation as a tool for systematic problem solving in non-computer-science disciplines. Introductory programming skills. Not for students with existing credit for or exemption from CPSC 110 or APSC 160. No programming experience expected.
- STAT 200 (3) Elementary Statistics for Applications: Classical, nonparametric, and robust inferences about means, variances, and analysis of variance, using computers. Emphasis on problem formulation, assumptions, and interpretation.
- STAT 241 (3) Introductory Probability and Statistics: Probability models, random variables and vectors, estimation, testing, regression, analysis of variance, goodness of fit, quality control.
- STAT 251 (3) Elementary Statistics: Probability, discrete and continuous random variables, joint probability distributions, estimation, hypothesis testing, regression, analysis of variance, goodness of fit.
- STAT 302 (3) Introduction to Probability: Basic notions of probability, random variables, expectation and conditional expectation, limit theorems.
- MATH 100 (3) Differential Calculus with Applications to Physical Sciences and Engineering: Derivatives of elementary functions. Applications and modeling: graphing, optimization.
- MATH 221 (3) Matrix Algebra: Systems of linear equations, operations on matrices, determinants, eigenvalues and eigenvectors, diagonalization of symmetric matrices.
What are the pre-requisites for the Computational Linguistics specialization?
In addition to the technical background required for all MDS students (see above), the expectation is that candidates will have a degree and/or other significant experience relevant to language. Candidates should outline this language background in their letter of intent.
Will you accept online courses (MOOCs, Coursera, Edx, etc.) as my pre-requisite courses?
- The UBC MDS program and Computational Linguistic specialization are very competitive programs. If you take your pre-requisite courses at an accredited university and submit the grades you receive on a transcript, you will have a stronger application compared to someone who has taken online courses (and does not have any grades to submit).
Would several years of work experience as a software engineer be accepted in place of the pre-requisite courses?
- While work experience is great in supporting your application package, we still require you to have university credit courses for the pre-requisites.
How are the applications reviewed? What do you look for in my application?
- The UBC MDS is a very competitive program. The Admissions Committee will review and consider all applications as a whole, including the mandatory prerequisites, personal interest statements, academic grades, academic/professional references, resumes and other experiences and English language tests (if applicable). See application tips here: https://ubc-mds.github.io/resources_pages/applicationAdvice/
What are the English language test requirements for international applicants from institutions where English is not the language of instruction?
- If your undergraduate degree was not completed at an English-speaking university, proof of English-language proficiency is required as this program requires a significant amount of reading, writing and oral communication. See the International Students page for more information on which English language proficiency exams we accept.
Does the program require a Graduate Record Examination (GRE)?
- The UBC Master of Data Science program does not require a GRE or any other academic test score for admission.
Can my references be professional rather than academic?
- Yes, the admissions committee will accept academic and/or professional references.
Fees and Financial Aid
What are the associated costs to the program?
- Tuition for the UBC Master of Data Science is comparable and competitive with other professional Masters programs at top domestic and international universities. All fees are in Canadian dollars (CAD):
- $31,836 CAD for domestic students (Canadian citizens and permanent residents)
- $43,709 CAD for international students
- Tuition for the Computational Linguistic specializaton is the same as the MDS program
- On acceptance into the program, students will be required to pay a $3,000 CAD non-refundable deposit
- On acceptance into the Computational Linguistics specialization, students will be required to pay a $1,000 CAD non-refundable deposit.
Aside from tuition fees, what other fees do I need to pay?
- For tuition fee information please see: https://masterdatascience.ubc.ca/admissions/tuition-and-financial-aid. In addition to tuition fees there are application fees (https://www.grad.ubc.ca/prospective-students/application-admission/online-application-fee) and student fees all UBC students pay: https://www.grad.ubc.ca/prospective-students/tuition-fees-cost-living/graduate-student-fees
What kind of scholarships, grants or financial assistance are available to students?
- The UBC MDS Vancouver and Okanagan campuses as well as the Computational Linguistic specialization offer the same merit-based entrance scholarships: $5,000 CAD awarded to a Canadian student and an international student. The admissions committee makes the selections based on the strength of students’ applications. No separate applications or documents are required. Learn more.
- Vancouver Campus only scholarship:
- The Mastercard Foundation (MCF) Scholars program - These scholarships target individuals from Sub-Saharan Africa who are academically talented but face economic disadvantages that prevent them from getting access to relevant and high-quality university education. After graduation, the MCF scholars use their experience and knowledge to contribute to economic growth and social development in their home countries. Learn more.
How long will it take for my application to be processed?
- Once the application deadline has passed, application processing will generally take between six and eight weeks. However, certain circumstances can cause that timeline to increase.
How does the capstone project work/will you help me find a capstone partner?
- The last two months of the program students work in teams of 3-5 on a project with an industry partner. This project ties all your learning in the program together and is a key launching point into your data science career. Students are assigned to a team and a capstone partner based on their preferences and can also suggest partners they would like to work with.
What employment opportunities are available after I complete the MDS degree at UBC?
Most of our graduates work as Data Scientists, Data Analysts, Data Engineers, Machine Learning Engineers, NLP Engineers, etc. Employers include governments, non-profits, large tech companies, start-ups, etc. in a wide variety of industries. For employment outcomes, please see: https://masterdatascience.ubc.ca/why-ubc/students-alumni.
- UBC Vancouver/Computational Linguistics: Vancouver offers strong connections with industry partners in public and private sectors, start-ups, and leading tech companies offer a wide range of networking/career opportunities.
- UBC Okanagan: UBC’s Okanagan campus borders the city of Kelowna – a hub of economic development, often deemed the “Silicon Valley of the North.” With it’s 2,000 tech start-ups and 24% growth in tech businesses over the last five years, the Okanagan campus provides extensive career and networking opportunities.
What career and professional development support is there in the program?
- Career and professional development and support is provided throughout the 10 months of the MDS program by a dedicated MDS Career Advisor. The MDS Career Advisor meets with students one-on-one throughout the length of the program. In addition, the Career Advisor facilitates resume and cover letter writing, technical interviewing, and networking workshops during the program’s second term. Other career and professional development support includes many industry talks, networking events and career fairs. Please see alumni information at these sites: