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
Successful candidates shall have strong backgrounds in Statistics and Computing Science. Ideal candidates would have a degree majoring in Statistics, and minoring in Computer Science or vice versa. At the least, we expect students to have several dedicated undergraduate courses in Statistics and several dedicated undergraduate courses in Computer Science. Note that most of applied statistical courses in engineering or MOOC statistical courses will not be considered to be eligible.
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. You will receive a link with the reference forms to provide to your referees from the Admissions Office once your application has been received.
Official academic transcript(s) from all prior post-secondary institutions attended — sent directly to Thompson Rivers University from the institution.
Supervisor requirement: Students pursuing the Thesis Option must have a confirmed faculty supervisor for their master’s thesis. You can explore the research areas of available faculty and contact a potential supervisor in the area of intended research. Communication with prospective supervisor on research topics, study plan and financial support are strongly encouraged. Students choosing Thesis Option must have a committed supervisor (before or after submitting application), and shall inform Admission Office the name(s) of confirmed faculty supervisor. Otherwise, their applications will be considered as “incomplete” and will not send to MScDS Admission Committee for assessment. If you have questions, please contact the program coordinator.
- Students who meet the minimum of academic requirements but are lacking some key knowledge/skills may be required to take preparation courses (which may be taken along with some graduate courses concurrently). Successful completion (i.e., grade B- or better) of preparatory courses will be a requirement to remain in the program and such courses will not be counted as graduate credits towards the MSc Data Science program. The admission committee in consultation with the program coordinator would determine the courses that would need to be taken in order to increase the chance of success in the MSc Data Science program.
- The knowledge indicated in the pre-requisites listed above is the absolute minimum for success in the program. We strongly encourage students to include the Knowledge Mapping Form in their application package to indicate which courses or experience they have from all topics listed in the Knowledge Preparation page. Missing or inappropriately completed knowledge mappings are generally viewed unfavourably by the admissions committee. Click here for a sample of the mapping form.
- Students who only have the bare minimum above are unlikely to obtain admission. Competitive candidates will have a unique, dedicated course for most of the items listed on the third page of the Knowledge Mapping Form, the column labelled as "desirable knowledge and skills".
- It is the candidate's responsibility to convey to the admissions committee that the listed course covers the material in the "heavily covered depth" listed on the Knowledge Mapping Form. If it is not obvious to the admissions committee by the title of the course, the committee will pass over the application unless clarifying information is provided (e.g., official course outline or explanation in personal statement). Courses that only touch on the content in the Knowledge Mapping will be viewed unfavourably by the committee and should be omitted.
- Applicants are encouraged to provide supplementary documents such as a CV and Research Statement/Additional Qualification information, if such documents contain additional information which are helpful for evaluation of the eligibility of applicants. Students should limit submission documents to information supporting preparedness for the four core courses (Program Structure), and should not submit anything akin to a biographical sketch of statement of interest. In unusual circumstances, an interview may be required by the committee as part of the admissions process.