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: 

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: 

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: 

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: 

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: 

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!