The listed courses are newly offered by the Faculty of Science in 2025.
You can review how to find more course details in Workday, including a tutorial to access the course schedule, key terminology you will encounter, and more. You can also refer to resources for course registration, such as degree requirements and managing courses in Workday.
BIOL_V 307: Natural History Collections and Biodiversity Science (3 credits)
This course is an introduction to biodiversity and specimen-based science, including theory and best practices for creating, curating and preserving natural history collections, working ethically with collections, and the historical, contemporary and future role of these collections to science and society.
ENVR_V 100: Exploring Environmental Science (3 credits)
Get an introduction to topics in earth science, ecology, human health, and energy from an environmental science perspective.
ENVR_V 205: Environmental Science in Practice I (1 credit)
Cover community building, land connections, and academic and career planning in environmental science.
ENVR_V 240: Environmental Problem Solving (3 credits)
Utilize practical and theoretical approaches to tackle complex environmental challenges, with emphasis on critical thinking while analyzing real-world issues.
ENVR_V 305: Environmental Science in Practice II (1 credit)
Explore mentorship, incorporating feedback, strengthening land connections and academic and career planning within the field of environmental science.
ENVR_V 350: Applied Environmental Ethics (3 credits)
Address the complexities of socio-ecological issues facing practitioners of environmental sciences including ethics and social equity.
ENVR_V 450: Environmental Policy and Law (3 credits)
Learn about the creation, implementation, and enforcement of environmental laws and policies at the international, national, and sub-national levels. Examine and critique laws, principles, and policies dealing with issues such as climate change, pollution, and biological diversity.
MATH_V 329: Introduction to Abstract Algebra (3 credits)
This course covers ideas and methods of group theory and their applications. Groups, subgroups, and cosets; homomorphisms, isomorphisms, and associated theorems.
MICB_V 305: Data Science in Microbiology and Immunology Research (3 credits)
Engage in this team-based data science research experience in microbiology and immunology.
NSCI_V 210: Research Design for the Neurosciences (3 credits)
Focus on research design relevant to the neurosciences, with an emphasis on engagement with the scientific process, from question formulation to knowledge translation.
STAT_V 405: Bayesian Statistics (3 credits)
Learn about Bayesian approaches to statistical inference, including probabilistic modelling, Bayesian inference workflows, approximation of posterior distributions supported by modelling languages, and analysis of Bayesian procedures and posterior approximation methods.
