Our Concentrations
Applied
Mathematics
What is Applied Mathematics?
As a discipline, Mathematics underlies the advances and insights of quantitative scientific domains. The techniques developed by mathematicians have proven to be invaluable for work in scientific computation, artificial intelligence, medical imaging, data compression and inference, quantum computing, theoretical economics, modern financial instrument pricing and modelling, computational biology, cryptography, communications, natural sciences, engineering sciences, and a host of others too numerous to mention.
Endless Career Opportunities
Irrespective of the concentration you are admitted to, all students follow the same timeline. For specific concentration course requirements.
Career Opportunities in Artificial Intelligence
- Big Data Engineer/Architect
- Business Intelligence Developer
- Consultant
- Data Scientist
- Deep Learning Engineer
- Machine Learning Engineer
- NLP Engineer
- Research Scientist
- Robotics Engineer
- Software Engineer/Architect
Program Requirements
Students must successfully complete six graduate level courses (totalling 3.0 Full Course Equivalents (FCEs)) as follows:
Two courses (1.0 FCEs) chosen from the Department of Mathematics course schedule. These must be MAT-1000 level courses or higher.
Two courses (1.0 FCEs) chosen from the Department of Computer Science’s (CSC designator) course schedule in two different groups. Course groupings can be found on the Computer Science website.
Two required courses (1.0 FCEs): Communication for Computer Scientists (CSC 2701H) and Technical Entrepreneurship (CSC 2702H).
An eight-month industrial internship, CSC 2703H (3.5 FCEs). The internship is coordinated by the department, and evaluated on a pass/fail basis. ‘Pass’ grades are awarded based on evaluations received from the industry/academic supervisors of the internship project and submission of an appropriately written final report, documenting the applied research internship.
