In the last few years, owing to the digitalisation and evolution of tech, organisations have been turning towards Data management, manipulation and analytics. Therefore, Data Science has gained huge popularity and is expected to stay relevant for a long time.
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The most common intakes are in the fall (September) and winter (January) semesters.
Tuition fees for masters in data science in Canada vary among universities but typically range from CAD 15,000 to CAD 40,000 per year for international students, which is considered affordable compared to the US or the UK.
Upon completing a masters in data analytics in Canada, you can expect promising career prospects and competitive salaries ranging from CAD 70,000 to CAD 100,000 per year.
Let’s dive into the details of masters in data analytics in Canada. Here’s all you need to know!
Universities and Fees for Masters in Data Analytics in Canada
University of Toronto
Ranked among the top universities globally, the University of Toronto offers a program in Masters in Data Analytics in Canada. Its curriculum combines mathematical and statistical foundations with machine learning techniques and data visualization.
The university’s strong emphasis on research and collaboration, along with its extensive industry partnerships, provides students with valuable hands-on experience.
| Application Deadline | Fall Intake – March |
| Duration | 2 years |
| Tuition Fee: | CAD 15,000 – CAD 50,000 per year |
University of British Columbia (UBC)
UBC also offers a Masters in Data Analytics in Canada, designed to equip students with the skills required to tackle complex data analysis challenges. The university boasts a multidisciplinary approach, incorporating computer science, statistics, and domain-specific knowledge.
UBC’s location in Vancouver offers a vibrant tech community and proximity to industry-leading companies.
| Application Deadline | Winter Intake – October |
| Duration | 10 months |
| Tuition Fee | CAD 30,000 – CAD 45,000 per year |
McGill University
Located in Montreal, McGill University is renowned for its research-focused approach. The Masters in Data Analytics program at McGill emphasizes applying data science techniques in real-world scenarios.
Students benefit from the university’s extensive partnerships with local industries and its state-of-the-art data science facilities.
| Application Deadline | Fall Intake – January |
| Duration | 1.5 years |
| Tuition Fee | CAD 25,000 – CAD 40,000 per year |
University of Waterloo
The University of Waterloo offers a masters in data analytics in Canada that integrates machine learning, data analytics, and big data techniques. Known for its co-op education system, students have the opportunity to gain practical experience through paid work terms.
The university’s strong ties with the tech industry in Canada’s technology hub, the “Silicon Valley of the North,” further enhance job prospects.
| Application Deadline | Fall Intake – January |
| Duration | 2 years |
| Tuition Fee | CAD 20,000 – CAD 35,000 per year |
Simon Fraser University
Simon Fraser University’s Master of Science in Big Data program equips students with the skills to extract insights from large datasets. The program focuses on the technical and business aspects of data science, providing a well-rounded education.
Located in the Vancouver metropolitan area, the university offers students opportunities to collaborate with leading tech companies and startups.
| Application Deadline | Fall Intake – January |
| Duration | 1.5 years |
| Tuition Fee | CAD 20,000 – CAD 35,000 per year |
University of Alberta
The University of Alberta’s Masters in Data Analytics in Canada prepares students for careers in data analytics, machine learning, and artificial intelligence. The curriculum emphasizes practical skills through hands-on projects and industry collaborations.
The university’s strong ties to the local tech community offer networking opportunities and access to cutting-edge research.
| Application Deadline | Fall Intake – March |
| Duration | 1.5 years |
| Tuition Fee | CAD 20,000 – CAD 30,000 per year |
York University
York University’s Master of Data Science and Analytics program focuses on applying data science techniques in various fields, including finance, healthcare, and marketing.
The curriculum covers areas such as statistical modelling, machine learning, and data visualization. York’s location in Toronto, a major tech and business hub, offers abundant opportunities for internships and industry collaborations.
| Application Deadline | Fall Intake – January |
| Duration | 2 years |
| Tuition Fee | CAD 15,000 – CAD 30,000 per year |
University of Ottawa
The Masters in Data Analytics program at the University of Ottawa focuses on data management, data analytics, and machine learning. The university’s proximity to the federal government and various research institutes provides unique opportunities for collaboration and internships.
The program emphasizes both theoretical knowledge and practical applications.
| Application Deadline | Fall Intake – January |
| Duration | 1.5 years |
| Tuition Fee | CAD 15,000 – CAD 25,000 per year |
McMaster University
McMaster University’s Master of Science in Data Science and Analytics program equips students with the necessary skills to analyze complex datasets and make data-driven decisions.
The program emphasizes a multidisciplinary approach, incorporating statistics, computer science, and business elements.
McMaster’s strong industry connections and collaborative research initiatives provide valuable experiential learning opportunities.
| Application Deadline | Fall Intake – February |
| Duration | 1.5 years |
| Tuition Fee | CAD 15,000 – CAD 25,000 per year |
Ryerson University
Ryerson University’s Master of Data Science and Analytics program equips students with the skills to extract insights from complex data and contribute to data-driven decision-making.
The program emphasizes hands-on experience through industry projects, internships, and a capstone research project. Located in downtown Toronto, Ryerson offers proximity to various tech companies and networking opportunities.
| Application Deadline | Fall Intake – January |
| Duration | 2 years |
| Tuition Fee | CAD 15,000 – CAD 30,000 per year |
Please note that the application deadlines and program durations may vary slightly from year to year.
The tuition fee highly depends on the course you choose and additional factors. It’s essential to check the official websites of the universities for the most up-to-date information.
Even better, connect with our experts and get an accurate cost estimation, eligibility guidelines, intakes, deadlines and more! Book a free conversation with us today.
Also read: Minimum IELTS score for Canada 2023-2024
IELTS Exam Fee India 2023-2024
Masters in Data Analytics in Canada: Course Structure
Masters in Data Science in Canada offers a comprehensive curriculum that equips students with the necessary knowledge and skills to excel in this rapidly evolving field.
These programs typically blend theoretical foundations with practical applications, enabling students to analyze complex datasets, develop machine learning models, and extract valuable insights.
Here’s a table outlining the common course structure for a Masters in Data Analytics in Canada:
| Course | Description |
| Foundations of Data Science | Covers the fundamental concepts and techniques of data science, including statistics, probability, data manipulation, and exploratory data analysis. Students gain a solid understanding of the principles that underpin data science applications. |
| Machine Learning | Explores various machine learning algorithms and techniques, including supervised and unsupervised learning, regression, classification, clustering, and ensemble methods. |
| Data Visualization | Focuses on effective data visualization techniques and tools. Students learn to communicate insights and patterns discovered from data through charts, graphs, and interactive visualizations. |
| Big Data Analytics | Examines the challenges and techniques for processing and analyzing large-scale datasets. Students learn about distributed computing, data storage systems, and technologies such as Hadoop and Spark. |
| Data Ethics and Privacy | Explores the ethical considerations and legal frameworks surrounding data science, including privacy, security, bias, and fairness. Students learn to navigate ethical dilemmas and develop responsible data practices. |
| Capstone Project | Involves a significant research or industry-focused project where students apply their skills and knowledge to solve a real-world data science problem. |
Masters in Data Analytics in Canada typically span 1.5 to 2 years, depending on the university and program structure. The coursework provides a balance between theoretical concepts and hands-on practical experience.
Students often have the opportunity to work on industry projects, internships, or research collaborations, allowing them to gain valuable insights and establish connections within the data science community.
The curriculum is designed to equip graduates with the expertise needed to thrive in diverse roles such as data scientist, data analyst, machine learning engineer, and business intelligence analyst.
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Career Outcomes for Masters in Data Analytics in Canada
Upon completing Masters in Data Analytics in Canada, graduates have a wide range of career opportunities available to them. The program equips them with the skills and knowledge required to excel in various data-driven roles across industries. Here are some common roles that graduates can pursue:
- Data Scientist: Data scientists analyze and interpret complex datasets to extract actionable insights and develop predictive models.
- Data Analyst: Data analysts focus on collecting, cleaning, and organizing data to provide meaningful insights and support decision-making processes.
- Machine Learning Engineer: Machine learning engineers design and implement algorithms and models that enable machines to learn from data and make accurate predictions or decisions.
- Business Intelligence Analyst: Analysts use data visualization and reporting tools to analyze and present data to support strategic business decisions.
- Data Engineer: Data engineers design and maintain the systems and infrastructure required to collect, process, and store large volumes of data.
- AI Research Scientist: AI research scientists work on cutting-edge research and development of artificial intelligence technologies, including natural language processing and computer vision.
Here’s a table showcasing some common data science roles along with their average salaries (figures are approximate and may vary):
| Designation | Average Salary (CAD) |
| Data Scientist | $90,000 – $120,000 |
| Data Analyst | $65,000 – $85,000 |
| Machine Learning Engineer | $100,000 – $130,000 |
| Business Intelligence Analyst | $70,000 – $95,000 |
| Data Engineer | $80,000 – $110,000 |
| AI Research Scientist | $100,000 – $150,000 |
| Data Consultant | $90,000 – $120,000 |
| Data Product Manager | $95,000 – $125,000 |
| Predictive Analyst | $75,000 – $100,000 |
| Quantitative Analyst | $90,000 – $120,000 |
Top Companies that Recruit Graduates of Masters in Data Analytics in Canada
Regarding employment, numerous top companies in Canada actively seek graduates with expertise in data science. Some notable employers include:
- Shopify
- Amazon
- Microsoft
- IBM
- RBC (Royal Bank of Canada)
- TD Bank
- Deloitte
- Accenture
- NVIDIA
Please note that salaries can vary based on factors such as location, years of experience, and the specific industry or company.
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Conclusion
In conclusion, pursuing a Masters in Data Analytics in Canada offers a pathway to a rewarding and in-demand career. The programs in Canada provide a comprehensive curriculum that covers essential topics such as statistics, machine learning, data visualization, and big data analytics.
Graduates of these programs can expect a wide range of career opportunities, including roles such as data scientists, data analysts, machine learning engineers, and business intelligence analysts.
Canada’s post-graduate work visa and permanent residence options are highly encouraging to international students. Most graduates who study Masters in Data Analytics in Canada stay back in the country to pursue a fulfilling career.
Planning to move to Canada to study? Here’s how Leap can help you:
- Do a detailed profile analysis, and match you with a list of universities
- Apply to the universities, including SOP and LOR writing
- Track the progress of the application and keep you informed
- Help you secure a student visa
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Frequently Asked Questions
Q. What is the average cost of studying Masters in Data Analytics in Canada?
Ans. The average cost for an Indian student to study a Master’s in Data Analytics in Canada is around 15,676.29 CAD per year. This estimate covers tuition fees and associated expenses, but costs can vary depending on the university and location.
Q. What is the average salary package for Data Science postgraduates in Canada?
Ans. Entry-level Data Science postgraduates in Canada typically earn between 80,000 and 120,000 USD per year. Salaries can vary widely depending on factors such as the company size, industry, location, and individual skills or experience. Additionally, benefits and bonuses may also impact the overall compensation package.
Q. What are the basic requirements for pursuing a Masters in Data Science in Canada?
Ans. Students applying for a Masters in Data Science (MDS) must have a minimum of a bachelor’s degree in computer science, statistics, mathematics or any related field. Basic knowledge of programming concepts such as Java and Python is also required.
Q. What are the different courses offered by universities in Canada in the field of Data Science?
Ans. Universities in Canada offer courses such as Decision Analytics, Data Mining and Visualisation, Data Analysis, Statistical Inference and Computing, Big Data Analytics, Big Data Systems, Machine Learning, Master of Data Science and Artificial Intelligence, among many others.
Q. What are the top universities in Canada for a Masters in Data Science?
Ans. Some top universities in Canada offering Masters in Data Science programs include the University of Toronto, the University of British Columbia, McGill University, and the University of Waterloo.
Q. Can I pursue a Masters in Data Analytics in Canada without taking the GRE?
Ans. Yes, some universities in Canada do not require GRE scores for admission to their Masters in Data Science programs. However, the admission requirements may vary, so it’s best to check with each university.
Are any part-time or online options available for a Masters in Data Analytics in Canada?
Ans. Yes, some universities offer part-time or online programs for a Masters in Data Science in Canada. This provides flexibility for working professionals or those who prefer a remote learning environment.
Q. How long does it take to complete a Masters in Data Analytics in Canada?
Ans. A Master’s in Data Analytics in Canada typically takes 1.5 to 2 years to complete. The exact duration depends on the university and the specific program structure, including whether the program is full-time or part-time. Some universities offer accelerated options or co-op placements, which might affect the total time required for completion.
Q. What career opportunities are available after completing a Masters in Data Analytics in Canada?
Ans. Graduates can pursue various roles such as data scientist, data analyst, machine learning engineer, business intelligence analyst, and data consultant across industries like finance, healthcare, technology, and consulting.
Q. Can I work while pursuing a Masters in Data Science in Canada?
Ans. Yes, international students in Canada can work part-time while pursuing a Master’s in Data Science. With a valid study permit, you can generally work up to 20 hours per week during the academic session and full-time during scheduled breaks. This opportunity can help me manage living expenses and gain relevant work experience.
Q. Can I apply for a Masters in Data Science program in Canada with a non-technical background?
Ans. Yes, some universities offer Masters in Data Science in Canada that are designed to accommodate students from diverse backgrounds. However, having some foundational knowledge in programming and statistics may be beneficial.
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