Master of Science in Data Science (MScDS)

The Master of Science in Data Science (MScDS) is normally a 2-year program. The goal of the program is to provide students with solid knowledge, techniques, and experience in the research and application of data science, and to prepare students to become researchers and leaders in the emerging area of data science at the regional, national, and global levels.

The program is unique in that it can be an application-orientated or a research-orientated master's program depending on whether students choose the Graduate Project option or the Graduate Thesis option. Regardless of their choice, graduates will develop the strong data analytics, critical-thinking, communication, and interpersonal skills required for success as a data scientist in big data or to pursue further advances in research.

Acceptable four (4) 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, or
a minimum iBT score of 88 with no section below 20, or
IELTS of at least 6.5 with no band below 6.0, or
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.