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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.

General

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 60, leaving students with a strong network of peers. Industry partners include numerous organizations and companies within the Okanagan region, which is home to 2,000 tech start-ups, as well as organizations throughout Canada such as Interior Health, ScotiaBank, and Statistics Canada.

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.

No, at this point, you cannot transfer between programs.

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.

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 2022/23 Okanagan cohort:

  • 57% identify as female
  • from: Canada, Bangladesh, China, Hong Kong, India and Taiwan
  • 40% of the class of 2023 enter the program with 3+ years of work experience
  • have past educational experience in: computer science, data science, engineering (civil, computer science, electrical, mechanical), business administration, accounting, risk management, international business, psychology, biology

Offered at the Vancouver campus, the Computational Linguistic program 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.

Unfortunately, the answer is no. These programs are professional 10-month master's programs offered on the Vancouver and Okanagan campuses. They give you access to key experts with the field of arts (linguistics), computer science, and statistics. As well, the programs provide strong connections with industry partners in public and private sectors, start-ups, and leading tech companies leading to a wider range of networking/career opportunities.

Because the MDS is a cohort-based program, we have only one intake per year in September. All of 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.

Application

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).

No. The prerequisite 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. Click on the tabs to review the prerequisites for each campus.

Vancouver

Please note: These are examples of the UBC equivalent courses

  • 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.

Okanagan

Please note: These are examples of the UBC equivalent courses

  • COSC 111 (3) Computer Programming I: Introduction to the design, implementation, and understanding of computer programs. Topics include problem solving, algorithm design, and data and procedural abstraction, with emphasis on the development of working programs
  • COSC 123 (3) Computer Creativity: A hands-on introduction to programming and computer-based problem solving and creativity. Experience with application development including storytelling, graphics, games, and networking.
  • DATA 301 Introduction to Data Analytics: Regression, classification, resampling, model selection and validation, fundamental properties of matrices, dimension reduction, tree-based methods, unsupervised learning.
  • STAT  121 (3) Elementary Statistics: Descriptive and inferential statistics, elementary probability, probability distributions, estimation of parameters, hypotheses testing, correlation, linear regression.
  • STAT 124 (3) Business Statistics: Probability models, random variables and vectors, estimation, testing, regression, analysis of variance, goodness of fit, quality control.
  • STAT 230 (3) Introductory Statistics: Applied statistics for students with a first-year calculus background. Estimation and testing of hypotheses, problem formulation, models and basic methods in analysis of variance, linear regression, and non-parametrics. Descriptive statistics and probability are presented as a basis for such procedures.
  • 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.

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 (i.e. a major or minor in linguistics). Candidates should outline this language background in their letter of intent.

The language background requirement for the MDS CL program refers to the study of natural language, and not programming languages.

The UBC MDS program and Computational Linguistic are very competitive programs. If you take your prerequisite 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). Online MOOCs/Coursera courses and adult education/continuing studies courses are not accepted but distance education courses are.

While work experience is great in supporting your application package, we still require you to have university credit courses for the pre-requisites.

The UBC MDS program is a very competitive program. The Admissions Committee will review and consider all applications as a whole, including the mandatory prerequisites, personal interest statements, transcripts for all current and previous post-secondary study, academic/professional references, resumes and other experiences and English language tests (if applicable). See application tips here.

If your undergraduate or graduate 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.

The UBC Master of Data Science program does not require a GRE or any other academic test score for admission.

As the MDS program does not require GRE/GMAT scores, you cannot use them to make up for a low GPA.

MDS will accept professional references instead of academic references but strongly encourages at least one academic reference. The goal of the reference should be to highlight your skills and suitability for the program. References should be selected based on how they can promote your abilities, not simply based on the reference's position or reputation.

The deadline to receive all reference letters is 7 days after the application deadline.

Fees and Financial Aid

  • Tuition Fees:
    • For the most up to date tuition fee information for the UBC Master of Data Science program, please visit our tuition page. Tuition for the UBC Master of Data Science in Computational Linguistics is the same as the MDS program.
  • Deposit Fees:
    • For the most up to date deposit fee information, please visit our tuition page.

In addition to tuition fees there are application fees and student fees all UBC students pay. Please note, tuition fees do not include room and board.

  • The UBC MDS Vancouver and Okanagan campuses as well as the Computational Linguistic program offer the same merit-based entrance scholarships: $25,000 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:
    • Master of Data Science Scholarship for Indigenous Students - Scholarships of up to the full cost of tuition have been made available annually by the Master of Data Science program for outstanding domestic or international students in the Master of Data Science program who identify as Indigenous. The scholarships are made on the recommendation of the Master of Data Science Admissions Committee.

    • Master of Data Science Scholarship for Black or Person of Colour Students - Scholarships of up to the full cost of tuition have been made available annually by the Master of Data Science program for outstanding domestic or international students in the Master of Data Science program who identify as Black or a Person of Colour. The scholarships are made on the recommendation of the Master of Data Science Admissions Committee.

After Applying

Once the application deadline has passed, application processing will generally take between eight and 12 weeks (this may vary by program). However, certain circumstances can cause that timeline to increase.

Capstone

During the last two months of the MDS programs, students work in teams of 3-5 with an external capstone partner and a UBC mentor to address a question facing the capstone partner’s organization using data science. They have the opportunity to gain real-world work experience and use real-world data sets. The capstone project ties all the learning in the program together and is a key launching point into a data science career. Note: The capstone is a 6-credit course, not an internship or co-op position. Students work in teams, are mentored throughout the process, and are awarded a grade at the end of the course.

Yes, we have developed and will continuously develop strong relationships with partners who are interested in participating in capstone. Students meet potential capstone partners and learn about their proposed projects and are given the opportunity to indicate with which capstone partners they prefer to work. They are assigned to a capstone team based on their preferences. Students can also suggest partners they would like to work with.

Capstone partners may have job opportunities afterwards, for which students are welcome to apply.

Career

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 our Student and Alumni page.

  • 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.

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:

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