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Where To Study Data Science In Canada

 1 year ago
source link: https://ceoworld.biz/2023/03/08/where-to-study-data-science-in-canada/
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Where To Study Data Science In Canada

Canada is a highly-sought study destination for international students, thanks to its quality of education and the convenient immigration system. According to U.S. News and World Report, Canada is the third-best country regarding quality of life. No wonder Canada is home to more than 600,000 international students. The world has only started to acknowledge the indispensable role of data for organizations to make informed decisions based on data. The salary of a data scientist is higher than that in most countries.
The best universities to study Data Science in Canada are:

  1. Ryerson University – Toronto, ON
    QS World University Ranking: Not ranked
    The uniquely developed data science program at Ryerson University facilitates the development of your interdisciplinary skills. At the same time, you gain deep technical and applied knowledge of data science and analytics. Once you finish this program, you will become a highly trained graduate ready to become a qualified data scientist by working in the government, industry, or research sectors.

  2. Carleton University – Ottawa, ON
    QS World University Ranking: 601-650
    The data science program offered by Carleton University teaches you theoretical knowledge, the practical application of theoretical knowledge, and the development of methods using data analysis. The program provides significant hands-on experience because of the projects you get to work on. The Data Science Laboratory takes the concept of practical coursework even further.

  3. Simon Fraser University – Burnaby, BC
    QS World University Ranking: 328
    Simon Fraser University, popularly known as SFU, is one of the first universities to create an undergraduate Data Science program in Canada. The program was formulated by including the most highly sought-after data science skills in the job market. While most data science programs stick to the essential coursework of computing science, mathematics, and statistics, SFU’s data science program also includes business coursework. This will help you to transition into a working professional that can be effective in the real world.

  4. University of Western Ontario – London, ON
    QS World University Ranking: 172
    University of Western Ontario’s Data Analytics program was designed to make you a technically sound professional who is set to pursue a career in data science and analytics. The program helps establish a solid foundation of computer science and statistics competencies. This will facilitate your development as a professional with in-demand interdisciplinary data science and analytics skills.

  5. University of Waterloo – Waterloo, ON
    QS World University Ranking: 154
    When you pursue a data science program offered by the University of Waterloo, you learn how to develop and apply methods that enable you to extract insights from available data. You can use this data to understand, project, and improve pursuits such as business strategy, manufacturing processes, marketing strategies, etc.

  6. University of British Columbia (UBC) – Vancouver, BC
    QS World University Ranking: 47
    The University of British Columbia, also known as UBC, is one of the most reputed universities in Canada. UBC’s Master’s program in Data Science was created to address the dearth of data science professionals in the market. This program will equip you with the technical knowledge, practical skills, and confidence needed to apply the learned lessons in the real world.

  7. University of Toronto – Toronto, ON
    QS World University Ranking: 34
    The University of Toronto is one of the most prestigious universities in Canada. The Data Science program offered by the university offers in-depth training in advanced statistical modeling, natural language processing, and machine learning. You will also learn fundamental content in data security, compliance, and privacy issues; programming languages and software used in data extraction and analysis; and neural networks and deep learning. By the end of the course, you will have learned how to visually represent data to help decision-makers understand the findings.

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