Master of Engineering (MEng) in Building Envelopes and Structures (BEST)
The Master of Engineering (MEng) in Building Envelopes and Structures (BEST) at Univers...
Master of Engineering in Applied Data Science (MADS)
Victoria
INTAKE: Jan & Sept
Program Overview
The Master of Engineering in Applied Data Science (MADS) at University of Victoria is a professionally oriented graduate program designed to equip students with advanced skills in data science, machine learning, and analytics. Located in Victoria, the program focuses on real-world problem solving and industry-relevant applications of data science. It is ideal for students with backgrounds in engineering, computer science, mathematics, or related disciplines who want to transition into high-demand data-driven roles. The program emphasizes practical training, enabling graduates to apply data science techniques across sectors such as technology, healthcare, finance, and environmental science.
Curriculum: The MADS curriculum combines theoretical foundations with hands-on learning to ensure a comprehensive understanding of applied data science. Core areas of study include data analysis, statistical modeling, machine learning, data visualization, and big data technologies. Students also gain proficiency in programming languages such as Python and R, along with tools used for data processing and analytics. The program typically includes project-based learning, case studies, and a capstone project where students apply their knowledge to solve real-world industry problems. This structure ensures that graduates are job-ready with strong technical and analytical capabilities.
Research Focus: Although the MADS is a professional engineering program, it incorporates applied research elements that allow students to explore emerging areas in data science. Key research themes include artificial intelligence, predictive analytics, data-driven decision-making, and interdisciplinary applications such as environmental data analysis and health informatics. Students work on projects that reflect current industry challenges, enabling them to develop innovative solutions while strengthening their research and analytical skills.
Industry Engagement: The University of Victoria maintains strong connections with industry partners, particularly within Canada’s growing technology sector. The MADS program integrates industry engagement through collaborative projects, guest lectures, and networking opportunities with professionals. Students benefit from exposure to real-world datasets and business problems, enhancing their practical experience. These industry links also support career development by providing insights into employer expectations and potential job opportunities in data science and analytics.
Global Perspective: The program attracts a diverse cohort of international students, creating a multicultural learning environment that reflects global data science trends. The curriculum is aligned with international industry standards, ensuring that graduates are prepared to work in global markets. Studying in Canada also provides access to a strong and growing tech ecosystem, offering opportunities for international graduates to build careers in a globally recognized education system. The University of Victoria’s emphasis on innovation, sustainability, and applied learning further enhances the global relevance of the MADS degree.
Location
Victoria
Score
IELTS 6.5
Tuition Fee
CAD 40050
Postgraduate Entry Requirements
Academic Qualifications: Applicants should have successfully completed a bachelor's degree or its equivalent from a recognized institution with a minimum overall score of 60% or equivalent.
English language proficiency:
- IELTS: Overall score of 6.5, with a minimum of 6.0 in each component
- TOEFL: Overall score of 90
- PTE Academic: Overall score of 72.
- DET Score: Overall score of 125, with a minimum of 105 in each component
- Some postgraduate programs may have specific subject prerequisites or additional requirements.
The University of Victoria in Canada offers several scholarships and financial aid opportunities to international students. These scholarships recognize academic excellence, leadership potential, and contributions to the community.
International Entrance Scholarships: The university offers a range of entrance scholarships specifically for international students. These scholarships are awarded based on academic merit. International students are automatically considered for these scholarships upon admission.
President's Scholarship for International Students: This prestigious scholarship is awarded to exceptional international students entering their first year of study at the University of Victoria. This scholarship recognizes academic excellence, leadership potential, and involvement in extracurricular activities.
International Master's and Doctoral Scholarship: This scholarship is designed for international students pursuing a master's or doctoral degree at the University of Victoria. The scholarship provides a stipend to help cover living expenses and tuition fees. Recipients are selected based on academic excellence and research potential.
Faculty-specific Scholarships: Some faculties at the University of Victoria offer scholarships specifically for international students within their respective academic programs. These scholarships are awarded based on criteria established by each faculty and may vary in value and eligibility requirements.
Graduates of the Master of Engineering in Applied Data Science (MADS) at University of Victoria are equipped with advanced analytical, technical, and problem-solving skills that are highly valued across global industries. The program prepares students for diverse career opportunities in sectors such as technology, finance, healthcare, consulting, and government.
Data Scientist: Data scientists analyze large and complex datasets to uncover insights that support strategic decision-making. They apply machine learning, statistical analysis, and data visualization techniques to solve real-world problems.
Machine Learning Engineer: Machine learning engineers design, build, and deploy predictive models and algorithms. They focus on optimizing model performance and integrating AI solutions into production systems.
Data Analyst: Data analysts interpret structured data to identify trends and patterns. They create dashboards and reports that help organizations improve efficiency and make informed business decisions.
Business Intelligence Analyst: BI analysts transform raw data into actionable insights using visualization tools and analytics platforms. They support organizations in improving performance and identifying growth opportunities.
Big Data Engineer: Big data engineers develop and manage large-scale data processing systems. They work with technologies like distributed computing frameworks to ensure efficient handling of massive datasets.
Data Engineer: Data engineers design and maintain data pipelines, ensuring data is clean, accessible, and ready for analysis. They play a crucial role in supporting analytics and machine learning workflows.
Artificial Intelligence Engineer: AI engineers create intelligent systems that simulate human behavior, such as recommendation engines, chatbots, and automation tools, enhancing business operations and user experiences.
Quantitative Analyst (Quant): Quants use mathematical and statistical models to analyze financial data, assess risk, and develop trading strategies, particularly in banking and investment sectors.
NLP (Natural Language Processing) Engineer: NLP engineers develop systems that enable machines to understand and process human language, including applications like sentiment analysis, chatbots, and voice recognition systems.
Data Science Consultant: Data science consultants advise organizations on how to leverage data for business growth. They identify opportunities for implementing analytics and AI solutions to improve efficiency and innovation.
