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Masters in Data Science in Canada: Top Universities, Fees, Eligibility

Masters in Data Science in Canada: Top Universities, Fees, Eligibility
Alpina ChariMar 2, 2023

Masters in Data Science in Canada: Top Universities, Fees, Eligibility

Canada, is one of the most attractive destinations for international students. It is well known for its high quality of education and various co-op programs with great career prospects. It has quickly become one of the top destinations for students seeking quality education in the booming field of data science. In today’s data-driven world, data science has emerged as one of the most sought-after fields across industries, organizations are relying on data scientists to extract insights and make informed decisions. Pursuing a Masters in Data Science in Canada is an extremely rewarding and lucrative option for many aspiring students. There are many highly ranked universities that offer Master’s level Data science programs, including ones offered as specializations under Computer Science programs. 

In this article, we will delve deeper into the reasons why Canada is an excellent destination for pursuing a Master’s degree in data science. We will explore the benefits of studying in Canada, including the country’s exceptional education system, its strong research infrastructure, and its diverse job market. We will also highlight some of the top universities in Canada offering data science programs, the admission requirements, and the potential career paths for graduates. 

Overview of Masters in Data Science in Canada 

No. of Programs  10+ 
Degree Types  MDS, MSc, MScDS, etc. 
Duration of Study  10 months to 2 years 
Average Tuition Fees  30000 CAD to 50000 CAD

Why Study Master’s in Data Science in Canada? 

High-quality education: Canadian universities are known for providing high-quality education, and their data science programs are no exception. These universities are consistently ranked among the best in the world, and they offer cutting-edge programs and research opportunities, taught by experienced faculty members who are experts in their field.

Booming tech ecosystem: Canada has a thriving tech ecosystem, with many startups and established multinational companies in the field of data science, machine learning, and AI. This means that there are ample opportunities for internships, co-op placements, and employment after graduation.

Global recognition: A degree in data science from a Canadian university is highly respected and recognized around the world, which can open up many career opportunities for graduates.

Multicultural environment: Canada is a diverse and welcoming country, with a multicultural environment that encourages students from all backgrounds to thrive. Students have the opportunity to interact with people from different cultures and backgrounds, which can broaden their horizons and help them develop a global perspective.

Post-graduation work permit: International graduates from a Canadian university are eligible for a post-graduation work permit for up to three years after graduation. This can be a great way to gain work experience and potentially even transition to permanent residency in Canada.

High standard of living: Canada is consistently ranked as one of the best places to live in the world, with a high standard of living, an excellent healthcare system, and welcoming communities. 

Top Universities/Colleges for Masters in Data Science in Canada 

Here are some of the best master’s programs offered in top Canadian universities: 

University Name  Programs Offered  Duration of Study  Annual Tuition fees 2023/24 
University of British Columbia  Master of Data Science (MDS) 10 Months  52126 CAD 
University of Toronto  Master of Science in Applied Computing (Data Science Specialization) 2 years  73500 CAD
University of Waterloo  Master of Data Science and Artificial Intelligence  1 year  40800 CAD
University of Calgary  Master of Data Science and Analytics  1 year “ 49368 CAD 
University of Alberta  M.Sc. Statistical Machine Learning  1 year  23515 CAD 
St Mary’s University  M.Sc. in Computing and Data Analytics  16 months  37000 CAD 
Carleton University  Collaborative Masters in Data Science (along with another degree) 2 years  30990 CAD 
Thompson Rivers University M.Sc. in Data Science  2 years  38528 CAD
University of Guelph  Master of Data Science (MDS) 1 year  42000 CAD 
Simon Fraser University  M.Sc. in Professional Computer Science (Big Data) 16 months  23714 CAD 

Admission Requirements 

  • Bachelor’s Degree in a related field such as Computer Science, Mathematics, Statistics, etc., with a minimum academic performance (Most universities require a 3.0 GPA on a 4.0 scale or equivalent)
  • English Language proficiency certificate in standardized tests. (IELTS – 6.5, TOEFL iBT – 90) 
  • Some programs require work experience of up to a year in a related field. 
  • Previous Academic Transcripts. 
  • Letters of Recommendation
  • Some programs might require additional admission requirements, such as Technical interviews and a Statement of Purpose. 

Cost of Studying Masters in Data Science in Canada 

The tuition cost for a Master’s in Data Science varies according to the institution, course type, duration, etc. But, on average, the tuition fees range from 30000 CAD to 50000 CAD. The cost of living, for most students, the cost ranges from 15000 CAD to 20000 CAD in a year. It mainly depends on various factors such as lifestyle, city of residence, accommodation type, and so on. Many students also take up part-time jobs while working to offset some of the costs. 

Here is the breakdown of some of the monthly expenses in Canada for students: 

Expense Type  Average Monthly Cost 
Accommodation  400 – 600 CAD 
Food  200 – 300 CAD
Transportation  100 – 150 CAD
Utilities (Internet, Phone, etc.) 50 – 100 CAD
Miscellaneous expenses  100 – 150 CAD

Job Opportunities for Data Science Graduates in Canada 

Data Science is a rapidly growing field, and graduates with a Masters in Data Science in Canada can find job opportunities in a variety of industries. Here are some of the most common job roles for data science graduates and their average annual salaries according to

Job Type  Average Annual Salary 
Data Scientist  89307 CAD
Machine Learning Engineer  101783 CAD
Data Engineer  96283 CAD
Business Intelligence Analyst  75079 CAD
Data Analyst  63852 CAD
Database Administrator  74675 CAD
Data Architect  106299 CAD


In conclusion, pursuing a Masters in Data Science in Canada can open up numerous exciting career opportunities in a rapidly growing field. Canada is home to some of the top universities offering world-class education in data science, with programs that are designed to equip students with the technical and analytical skills needed to succeed in the industry. With a high demand for skilled data scientists in Canada and globally, graduates of data science programs in Canada can expect to have a range of career options to choose from. 

Moreover, Canada’s supportive and diverse academic environment, combined with its welcoming and multicultural society, make it an excellent destination for international students looking to pursue a Masters in Data Science. As such, a Master’s in Data Science in Canada can be a great investment for anyone interested in the field of data science, providing opportunities for personal growth, professional development, and a rewarding career. For more information, book a free consultation with our admission experts. You can also use our exclusive tool Gyanberry, a platform designed to simplify the entire admission process, from finding courses to applying to multiple universities simultaneously. 

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On average, the cost of studying for a Masters in Data Science in Canada ranges from 30000 CAD – 50000 CAD.

Admission requirements vary depending on the institution and the program. However, some of the common requirements include a Bachelor’s degree, English proficiency test score, Academic transcripts, Statement of Purpose, Letters of Recommendation, etc. 

Some of the most common job roles for Data Science graduates include Data Scientist, Data Architect, Data Analyst, Data Engineer, Machine Learning Engineer, Database Administrator, etc. 


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