Our Concentrations
Computer
Science
What is Artificial Intelligence?
As a discipline, Artificial Intelligence (AI) includes intellectual focus, such as knowledge representation, probabilistic and statistical theory, machine learning (deep learning), computational linguistics and natural language processing, computer vision, and robotics. AI is also being applied to a wide range of scientific domains, from medicine to the humanities. The efficacy of AI is embraced in industry as we witness rapid adoption from recommenders in e-commerce to self-driving vehicles in transportation. The Artificial Intelligence concentration is unique at the University of Toronto and has been the first to become the pre-eminent program in Canada due to the strength and expertise in our partnering academic units (Department of Statistical Sciences and the Faculty of Applied Science and Engineering).
Forbes has recently named Toronto as the most important AI hub in the world, “Toronto will establish itself as the most important AI hub in the world outside of Silicon Valley and China”. With Toronto as a global centre for AI research, it is little wonder multinational firms are establishing AI labs in the city while there is a burgeoning AI start-up and SME ecosystem within the Greater Toronto Area.
The Artificial Intelligence concentration offers students an advanced understanding of artificial intelligence, vigorous research training and the opportunity to test your knowledge in the real world through our applied research internship.
We invite students from a wide range of disciplinary backgrounds to apply but you must demonstrate a strong background in artificial intelligence – preferably through formal academic training at senior undergraduate level.
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:
Three graduate courses (1.5 FCE) must be chosen from the Department of Computer Science approved list in two different groups, including a maximum of 1 course from Group 2.
One graduate course (1.0 FCE) must be chosen from Group 1, 3, 4. At least two of the four courses must be taken from the Computer Science course schedule. While the other two are typically from the Computer Science course schedule, students have the flexibility to choose sufficiently technical graduate courses from other departments as well. 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.
