Acceptable four-year bachelor 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 thesis option
Preference will be given to students who have specialized in the areas of statistics, computing science, mathematics and engineering.
Prospective students are expected to demonstrate working knowledge of statistics, data structures and algorithms, databases and R/Python software packages. Examples of course work that demonstrates such knowledge at Thompson Rivers University are MATH 2110 (Calculus III), MATH 2120 (Linear Algebra), STAT 2000 (Introduction to Statistics) and COMP 1231 (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 reference from academics or professionals. Letters should comment on the applicant’s academic ability and record, training, research/work experience, in particular relating to statistics, programming, data analysis, machine learning, or AI. Please download the fillable Referee Form and send to your referees to fill, and the completed Referee Forms must be sent directly to Thompson Rivers University (international student sends to email@example.com; domestic student sends to firstname.lastname@example.org ) from the referees or institution.
Official academic transcript(s) from all prior post-secondary institutions attended — sent directly to Thompson Rivers University from the institution.
Note: Applicants are encouraged to provide supplementary documents such as CV, Research Statement/Statement of Purpose if such documents contain additional information which are helpful for evaluation of the eligibility of applicants.
Admission to the Master of Science in Data Science program will be determined by the candidate’s academic and professional record, letters of recommendation, areas of research interest and the ability of the faculty member to accept the student into their research group. MScDS Admission Committee will assess candidate’s qualification based on academic and professional record, letters of recommendation, areas of research interest and the ability of the faculty member to accept the student into their research group, and determine the suitability to the program and issue acceptance recommendation.
Students who do not meet the admission requirements may be required to take prerequisite courses. The admission subcommittee in consultation with the program coordinator would determine the courses that would need to be taken to meet the admission requirements.