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Explore Undergraduate Programs

Pursue a degree in general mathematics or actuarial science with the Department of Mathematics and Statistics.

Mathematics (major)

The Mathematics major explores the various branches of mathematics and statistics and their applications in the real world. During the course of your studies, much of your learning will occur while actively working on problems in class, during tutorials and in take-home written assignments. You’ll learn mathematical and statistical fundamentals and gain exposure to a variety of modern subdisciplines of these subjects including abstract algebra, analysis, biostatistics, differential equations, geometry, logic, number theory, machine learning, probability and stochastic processes.


Actuarial science (major)

How is the premium rate for flood insurance calculated? Can an insurance company cover all of their claims? What is the value of a company’s pension commitments? Actuarial science is concerned with the construction of models and solutions for financial, business, and societal problems involving uncertain future events. During the course of your studies, much of your learning will occur while actively working on problems in class and during tutorials. By exploring the complicated world of financial risk, this degree will equip you with the fundamental and practical tools you’ll need to assess and forecast risk in order to make sound financial decisions.

Financial data charts

General mathematics (major)

Combined with a Bachelor of Education through Werklund School of Education.

The emphasis of the general mathematics program is on the breadth of mathematical knowledge. Specifically, students in the general mathematics program have increased flexibility in selecting courses to meet their program requirements. This makes it highly attractive for students who wish to pursue another academic field of study to complement general mathematics.


Data science (minor / major)

In the world around us, people look for patterns and stories in data. In data science, we explore methods from statistics and computing in combination what we know from other subject areas to better understand our data and how to interpret our findings.  We learn to handle data more efficiently, the possibilities and limits of data-centric techniques such as machine learning, and the ways in which our humanity affects how we collect, curate and present data and stories from our immediate contexts to the world.


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