Features:

• Open to domestic and international students
• Hands-on, applied learning tied to real-world challenges, from agriculture to AI.

Deepen your understanding of computer science and learn to apply it to problems that matter. UFV’s 30-credit, full-time MSc combines advanced theory with practical applications in fields such as artificial intelligence, cybersecurity, data science, and agriculture.

You’ll begin with a shared foundation in research methods, algorithms, software design and architecture, and machine learning, then build on your interests through electives and supervised work. Pursue an original research thesis to prepare for research or doctoral study, or complete an applied project focused on solving a real-world computing problem.

Program outline

1. Complete 4 core courses (12 credits)

Complete these four courses first.

• COMP 701: Research Methods
• COMP 702: Design & Analysis of Algorithms
• COMP 703: Software Design & Architecture
• COMP 704: Machine Learning

2. Choose your program stream

Please note that the project stream is designed as a professional, industry-oriented option. If you wish to meet requirements for PhD admission, choose the thesis option instead.

3. Choose 2 or 3 elective courses

 A subset of the following elective courses will be offered each year. All courses are three credits.

• COMP 721: Advanced Special Topics in Computer Science
• COMP 722: Algorithms for Optimization
• COMP 723: Blockchain Foundations and Software Engineering
• COMP 724: Computational Complexity
• COMP 725: Computer Vision
• COMP 726: Cybersecurity Fundamentals
• COMP 727: Data Mining and Visualization
• COMP 728: Formal Software Development
• COMP 729: Natural Language Processing
• COMP 730: Network Systems
• COMP 731: Programming for loT systems
• COMP 732: Wireless Communications

• A 4-year bachelor's degree in computer science or a closely related field from a recognized institution.
• Cumulative GPA of at least 3.00 (4.33 scale) over the last 60 credits.
• Three references, on the approved reference form, submitted from institutional email addresses (references can be academic or professional).
• A personal statement of up to 1,000 words.
• English-language proficiency at the degree level (go to degree-level proficiency standards) in the Academic Calendar.
• Conditional admission may be available for applicants who are nearly, but not fully, qualified.
• No work-integrated learning / practicum is required for completion.
• No GRE or other placement/entrance test is required.

How to apply

This program is open for international students.

Graduates of a UFV master's may be eligible to apply for a post-graduation work permit, and depending on your program and current federal rules, your spouse or partner may also qualify for an open work permit. These rules are set by the Government of Canada and change often, so what applies to you depends on your situation and timing. UFV has an in-house team of regulated immigration advisors to support you once you're admitted.

• Learn how to apply as an international student

• Go to all programs open to international students

At the end of the program, graduates will be able to:

1. Design scalable and sustainable solutions to complex computing problems across diverse domains with a focus on agriculture, cyber security and data science.

2. Leverage emerging computer science technologies for evolving interdisciplinary business needs that prioritize ethical, responsive, and inclusive design principles.

3. Conduct research using appropriate methodologies, including experimental design, data-driven analysis, and computational simulations to applied and/or theoretical problems.

4. Disseminate findings to multiple audiences via technical reports, publications, data visualizations, or presentations applicable to the field of computer science.

5. Integrate Indigenous knowledge systems with Western methodologies to engage in ethical and culturally responsive development of computational systems for local and global contexts.

6. Apply computer science project management skills that highlight interdisciplinary collaboration, ethical decision-making, and leadership approaches to drive innovations.

7. Adopt lifelong learning strategies to stay current in the discipline and reflect on their role within the field as a computer science professional.

8. Apply critical thinking, problem-solving, and adaptability skills in computer science contexts.