In Canada, many industries, including finance, healthcare, technology, and retail, are increasingly relying on data science to drive business decisions. Additionally, Canada has a growing startup ecosystem and tech industry, with many startups and established companies looking for data scientists to help them gain insights and make data-driven decisions.
The Canadian government has also recognized the importance of data science, and various initiatives are underway to promote the growth of this field. For instance, the government has launched the Pan-Canadian Artificial Intelligence Strategy, which includes investments in research and development, talent development, and commercialization of AI technologie
Not only this, many top Canadian universities now offer data science programs, and there are numerous boot camps and online courses available for individuals looking to enter the field. And so, if you are looking forward to studying data science in Canada, you should be well assured of your future!
Moreover, to back you up with your research, we have come up with this blog on the best data science programs in Canada along with the top data science universities in Canada!
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Top 10 Data Science Universities in Canada
Canada is home to many world-class universities that offer excellent programs in data science. Many of these institutions offer a variety of degree programs, including undergraduate, graduate, and postgraduate degrees, as well as specialized certificates and diplomas in data science and related fields.
We have shared some of the best data science universities in Canada for you to explore:
University |
QS Ranking 2024 |
Tuition Fees (International) |
21 |
CAD 55,300 |
|
34 |
CAD 38,000 |
|
30 |
CAD 19,100 (per semester) |
|
111 |
CAD 28,010 |
|
112 |
CAD 31,815 |
|
141 |
CAD 18,978 (per year) |
|
318 |
CAD 27,382 |
|
182 |
CAD 29,158 |
|
353 |
CAD 29,962 |
|
Ryerson University |
801-1000 |
CAD 29,878 |
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Best Data Science Programs in Canada
Canada has a wealth of data science programs offered by various universities across the country. The programs vary in structure and focus, but generally include coursework in statistics, machine learning, programming, and data analysis, among other topics.
Some of the most popular data science programs in Canada are offered by universities such as the University of Toronto, the University of British Columbia, McGill University, the University of Waterloo, and the University of Montreal, among others. These programs are typically taught by experienced faculty members who are experts in the field and have experience working in various industries.
Given below are some popular data science courses in Canada:
University |
Degree/Course Name |
University of Toronto |
Master of Science in Applied Computing (Data Science) |
University of British Columbia |
Master of Data Science |
McGill University |
Master of Science in Data Science and Analytics |
University of Waterloo |
Bachelor of Mathematics in Data Science, Master of Data Science |
University of Montreal |
Bachelor of Data Science, Master of Data Science |
Simon Fraser University |
Bachelor of Science in Computing Science (Data Science) |
University of Alberta |
Bachelor of Science in Computing Science (Data Science) |
Ryerson University |
Bachelor of Science in Data Science and Analytics |
York University |
Bachelor of Science in Applied Mathematics (Data Science) |
University of Guelph |
Master of Applied Data Science and Analytics |
Carleton University |
Bachelor of Computer Science with a Concentration in Data Science |
McMaster University |
Master of Science in Mathematics and Statistics (Data Science) |
Data Science Programs in Canada Course Structure
Now to give you an idea of how typical data science courses in Canada look like, we have collated the most popular ones:
Name of Program |
Program Type |
Course Structure |
Credits |
Data Science and Analytics |
Master's Degree |
Mathematics for Data Science, Data Management, Machine Learning, Statistical Learning |
30 |
Bachelor of Science in Data Science |
Bachelor's Degree |
Mathematics for Data Science, Programming for Data Science, Data Management, Machine Learning, Data Visualization |
120 |
Data Science Certificate |
Post-Graduate Certificate |
Programming for Data Science, Machine Learning, Data Management, Big Data Analytics |
18 |
Master of Data Science |
Master's Degree |
Mathematics for Data Science, Programming for Data Science, Data Management, Machine Learning, Data Visualization |
30 |
Graduate Diploma in Data Analytics |
Graduate Diploma |
Mathematics for Data Analytics, Statistical Inference, Data Management, Machine Learning, Big Data Analytics |
12 |
Admission Requirements at Data Analytics Universities in Canada
Admission requirements for data analytics universities in Canada may vary depending on the program and university. However, here are some general admission requirements:
- Educational Background: Applicants are generally required to have a bachelor's degree or higher from a recognized institution. The degree should be in a relevant field such as computer science, mathematics, statistics, engineering, or a related field. Some programs may also accept applicants with relevant work experience in lieu of a degree.
- GPA: Many programs require a minimum GPA, typically around 3.0 (on a 4.0 scale) or higher. Some programs may require a higher GPA, depending on the competitiveness of the program.
- English Language Proficiency: International students whose first language is not English may be required to submit proof of English language proficiency. This can be done through tests such as TOEFL or IELTS.
- GRE or GMAT scores: Some programs may require GRE or GMAT scores, especially for master's programs.
- Work Experience: Some programs may require or prefer applicants to have relevant work experience in data analytics or a related field.
- Personal Statement or Letter of Intent: Many programs require a personal statement or letter of intent, where applicants are asked to outline their career goals and reasons for applying to the program.
Scholarships Available for Data Science Courses in Canada
There are various types of financial aid available for data science programs in Canada, including scholarships, bursaries, grants, and loans. Many universities offer their own financial aid programs, such as merit-based scholarships and need-based bursaries. Additionally, the Canadian government provides financial aid to eligible students through programs like the Canada Student Loans Program (CSLP) and the Canada Student Grant Program (CSGP).
Given below is an amalgamation of some of the most popular scholarships available to pursue data science programs in Canada:
Scholarship Name |
Amount Offered |
Eligibility Criteria |
Canadian Graduate Scholarship - Master's Program (CGS-M) |
$17,500 |
Canadian citizens or permanent residents enrolled in a master's program in data science or a related field, with a minimum GPA of 3.0. |
Natural Sciences and Engineering Research Council of Canada (NSERC) Postgraduate Scholarships |
$21,000 - $35,000 |
Canadian citizens or permanent residents enrolled in a doctoral program in data science or a related field, with a minimum GPA of 3.0. |
Mitacs Globalink Research Award |
$6,000 - $15,000 |
Undergraduate or graduate students from eligible countries (including Canada) enrolled in a data science research project. |
Ontario Graduate Scholarship (OGS) |
$15,000 |
Canadian citizens, permanent residents, or international students enrolled in a master's or doctoral program in data science or a related field, with a minimum GPA of 3.0. |
Queen Elizabeth II Graduate Scholarship in Science and Technology (QEII-GSST) |
$15,000 |
Canadian citizens, permanent residents, or international students enrolled in a master's or doctoral program in data science or a related field, with a minimum GPA of 3.7. |
Co-Op Programs for Data Science Programs in Canada
As cool as the name sounds, co-op programs in Data Science provide you with the opportunity to gain practical experience and build their skills in data analytics, machine learning, and related fields through alternating academic terms and work terms. These programs typically last for 4-5 years and involve multiple work terms with industry partners, allowing students to apply their classroom knowledge to real-world problems and develop valuable professional connections. Many universities in Canada offer co-op programs in Data Science, and we have listed the most popular ones below:
Program Name |
University |
Duration |
Credit |
Data Science Co-op |
University of Waterloo |
5 years |
20 academic terms + 5 work terms |
Co-op Data Science |
University of British Columbia |
5 years |
20 academic terms + 4 work terms |
Data Science Co-op |
Ryerson University |
4 years |
16 academic terms + 3 work terms |
Co-op Data Analytics |
Carleton University |
4 years |
16 academic terms + 4 work terms |
Applied Data Science Co-op |
Simon Fraser University |
4 years |
16 academic terms + 4 work terms |
Co-op Data Science |
University of Toronto |
4 years |
16 academic terms + 3 work terms |
Career Prospects at Best Data Analytics Universities in Canada
You as a graduate of data science in Canada can score a good average salary of CAD 81,000 per annum. Top recruiters at data analytics universities in Canada include Shopify, BMO, Microsoft, Amazon, Rogers Communications and more.
Given below are some popular job profiles along with their average salaries post pursuing data science programs in Canada:
University |
Job Profiles |
Average Salaries |
University of Toronto |
Data Scientist, Business Analyst, Data Analyst |
$77k - $111k |
University of British Columbia |
Data Analyst, Business Intelligence Analyst, Data Scientist |
$59k - $102k |
University of Waterloo |
Data Scientist, Machine Learning Engineer, Business Analyst |
$65k - $117k |
McGill University |
Data Analyst, Business Intelligence Analyst, Data Scientist |
$52k - $95k |
Simon Fraser University |
Data Analyst, Data Scientist, Business Analyst |
$60k - $103k |
Yocket Recommendations for Studying Data Science in Canada
So, in conclusion, if you're interested in studying data science in Canada, here are our top recommendations to help you get started:
- Research different programs: There are many universities and colleges in Canada that offer data science programs, each with its own unique curriculum and specializations. Research and compare different programs to find one that aligns with your interests and career goals.
- Consider co-op programs: Co-op programs provide students with the opportunity to gain practical work experience in their field while completing their studies. Consider enrolling in a data science program with a co-op component to gain hands-on experience and improve your job prospects after graduation.
- Build a strong foundation in math and programming: Data science requires a strong foundation in math and programming. Consider taking courses in calculus, linear algebra, statistics, and programming languages such as Python and R to prepare for your data science studies.
- Participate in extracurricular activities: Participating in extracurricular activities such as hackathons, coding clubs, and data science competitions can help you gain valuable skills and experience in data science, as well as connect with other students and professionals in the field.
- Seek out networking opportunities: Building a professional network can help you find job opportunities and advance your career in data science. Attend industry events and conferences, join data science groups on social media, and connect with professionals in the field on LinkedIn.
- Stay up-to-date with industry trends and developments: Data science is a rapidly evolving field, and it's important to stay up-to-date with the latest trends and developments. Subscribe to industry publications, attend webinars and workshops, and take online courses to continue learning and expanding your knowledge in data science.
And, if you have chosen a data science university in Canada for yourself, its time to connect with our Yocket Counselors to understand the steps ahead!