Program at a glance
Credential
Master
Faculty
Faculty of Science
Department
Engineering
Duration
2 Years
Program Delivery
On Campus
Location
Kamloops, B.C.
Program overview Design Tomorrow’s Technology
The amount of data in our world has exploded. And with it, so has demand for trained scientists and analysts able to make data-driven decisions.
Data scientists use mathematical, computational, statistical and algorithmic techniques to solve analytically complex data problems. In our Master of Science in Data Science (MScDS), you will engage in research and hands-on applications of data science in the classroom and through industrial projects, using cutting-edge techniques and algorithms. You will work on models of practical, existing problems to prepare you for situations you may encounter on the job and in the world.
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From code to career Real-world learning focus
The potential of big data comes with challenges and opportunities, as described by Canada's Big Data Consortium in the report Closing Canada's Big Data Talent Gap:
"Bold promises have been made for Big Data and Analytics (i.e., data science): exceptional customer insights; better decision-making; improved productivity and performance; and product and service innovation."But the promise of Big Data and Analytics faces a key constraint: a talent gap that is felt across all of Canada’s regions, sectors, and industries.
Our program builds upon the existing strengths of TRU’s Department of Mathematics and Statistics, Computing Science, and the Centre for Optimization and Decision Science at TRU, as well as the collaboration with other departments across campus and industry. Whether you're advancing your career, pivoting into tech, or preparing for doctoral studies, the Master of Engineering Science empowers you to engineer solutions that shape the future.
Upon Completion of the program, you will be able to:
- Use data investigation tools, including data cleaning, sampling, management and exploratory analysis.
- Use data exploratory methods to visualize high-dimensional data to identify trends and patterns in data sets.
- Implement foundational concepts of data computation: data structure, algorithms, simulation, and analysis.
- Integrate the techniques from mathematical modelling, optimization, machine learning, data mining and applied statistics to model big data sets to a workable frame for further data investigation.
- Apply advanced data analytical methods and algorithms to large data sets to extract meaningful insights.
- Design an analytic strategy to model a potential issue and find a knowledgebased solution for real-world challenges using public and private data sources.
- Communicate results of data analysis effectively (visually and verbally) to a broad audience.
Admission
Seats are limited, so applicants are encouraged to apply early. We process applications on an ongoing basis and will stop accepting applications when all seats are filled.
The MScDS program has ONLY one intake each year and our program does not offer a defer option for admission.
Admission detailsAdmission requirements
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.
All Admission RequirementsApplication deadlines
Domestic Students: August 01, 2026
International Students: January 15, 2026
Applications received after January 15 may be considered, but no extensions for paperwork like study permits, will be granted.
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Apply TodayMaster's scholarships
Ken Lepin Graduate Student Award 8 awards valued at $6,600 each
To be eligible, you must:
- be a Canadian citizen or permanent resident
- be entering first or second year of a full-time campus-based graduate studies program
Co-op Student Of the year 2020
The engineering program and university are two things I really believe in. I’m very excited to watch and help them grow.
— Lorelei Guidos Read more about the award
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