Acceptable four-year bachelor's degree or equivalent in a discipline of science, or a related discipline with a minimum average grade in the last 60 credits of:
- B (GPA of 3.00 on a scale of 4.33) for project option
- B+ (GPA of 3.33 on a scale of 4.33) for the thesis option
Successful candidates must have solid backgrounds in computing science and statistics. The best candidates will have a degree with a Statistics major and a Computer Science minor, or vice versa. At the very least, we anticipate that students will have taken several devoted college courses in computer science and statistics. Please take note that the majority of engineering courses that apply statistics or MOOC statistics courses will not be accepted.
Prospective candidates must demonstrate a working understanding of databases, R/Python software, statistics, data structures, and algorithms. At Thompson Rivers University, examples of coursework that exhibits this understanding are COMP 1231, MATH 2110 (Calculus III), MATH 2120 (Linear Algebra), STAT 2000 (Introduction to Statistics), and MATH 2110 (Calculus III) (Computer Programming II).
Applicants who did not complete their undergraduate degree in an English language university in a country whose first language is English must have one of the following:
- A minimum TOEFL score of 570 with a TWE of 4.5 or higher.
- A minimum iBT score of 88 with no section below 20.
- IELTS of at least 6.5 with no band below 6.0.
- CAEL of at least 70 with no subsets below 60.
Two letters of recommendation from academics or experts. Letters should make observations about the applicant's academic performance, training, and work experience, particularly as it relates to statistics, programming, data analysis, machine learning, or artificial intelligence (AI). Once your application has been submitted, the admissions office will send you a link with the reference forms to give to your referees.
Official academic transcript(s) from all prior post-secondary institutions attended — sent directly to Thompson Rivers University from the institution.
Students who choose the thesis option must have their faculty supervisor for their master's thesis confirmed. You can look through the faculty members' research specialties and get in touch with a potential supervisor who specializes in the field of your intended study. It is highly recommended that you communicate with your potential supervisor on study plans, research topics, and financial support. Students who opt for the thesis option must choose a supervisor (either before or after submitting their applications), and they must let the admissions office know who that faculty member is. Otherwise, their applications will be considered “incomplete” and will not send to MSc.DS Admission Committee for assessment. If you have questions, please contact the program coordinator.
Students who attain the basic academic standards but fall short on some essential information or abilities may be asked to enroll in preparatory courses (which may be taken along with some graduate courses concurrently). Preparatory courses must be completed successfully (i.e., with a grade of B- or higher) to continue in the program. These courses will not be applied as graduate credits for the MSc Data Science program. The courses that must be taken to increase the likelihood of success in the MSc Data Science program will be decided by the admission committee in consultation with the program coordinator.
