Data Science
Related Subject Areas:
- Instruction language
- English
- OUAC code
- RDT
- Degree
- Bachelor of Science, BSc
- Experiential learning
- Practicum or internship option available
- Enrollment
- 200
- Grade range
- 75-80%
Requirements
Prerequisites
- Six 4U/M courses
- ENG4U (minimum 60%)
- MHF4U and either MCV4U or MDM4U
Admission
Basic Requirements for Admission (Required for All Programs)
You must complete the requirements for the Ontario Secondary School Diploma (OSSD). A minimum average of 70% is required for consideration for admission. A minimum grade of 60% must be obtained in ENG4U. You must present a minimum of six 4U/M courses to be considered for admission.
Note: Some programs may have higher average and supplementary application requirements. Some programs may also require a minimum number of 4U/M courses.
Failed and Repeated Courses
If you repeat a course, the highest of the 2 grades will be used in the admission average calculation, if applicable.
Timing and Process for Admission Decisions
For full-time enrollment beginning in September, Trent University expects to send offers of admission on an ongoing basis starting in January.
You must complete or be registered in six 4U/M courses. Admission decisions will be made using grades from a minimum of 3 final 4U/M courses if you are in a semestered school, or 6 interim 4U/M courses if you are in a non-semestered school.
Grade 11 grades may be used to extend an early offer of admission when sufficient 4U/M grades are not available. All offers of admission are conditional, pending the successful completion of all OSSD requirements and prerequisites with satisfactory academic standing.
Notes
Working with and understanding big datasets is an essential skill required in nearly all business sectors today. There is a huge demand for graduates with both the computer science and sector-specific skills to analyze, understand and evaluate large sets of untapped data. Through Trent’s interdisciplinary approach to education, you’ll hone your skills in a focus area of your choice, while gaining a deeper understanding of data analysis, statistics and information management techniques, including programming, visualization and predictive modelling.



