Our Concentrations
Artificial
Intelligence
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 courses (1.5 FCEs) in the area of Artificial Intelligence.
- Two courses (1.0 FCEs) must be selected from the core list of AI courses (see list below).
- One course (0.5 FCE) must be chosen from additional AI courses outside the core list.
- One course (0.5 FCE) must be chosen from courses outside of AI in Groups 1, 3 or 4. 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).
- Students are permitted to choose a maximum of two courses (1.0 FCEs) from outside the Computer Science graduate course listing.
- 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.
- Students in the artificial intelligence concentration are permitted to choose a maximum of two courses (1.0 FCEs) from outside the Computer Science graduate course listing.
- Students in the artificial intelligence concentration may also request a waiver of an AI core course requirement by demonstrating mastery of equivalent material. All waivers are subject to approval of the Academic Director, Professional Programs. Note that such a waiver would allow students to take additional AI courses from outside the core list. In all cases, students must complete 1.5 FCEs in AI courses.
- All course selections should be made in consultation with and approved by the Program Director. Appropriate substitutions may be possible with approval.
- AER1513H – State Estimation for Aerospace Vehicles
- AER1517H – Control for Robotics
- CSC2501H – Computational Linguistics
- CSC2502H – Knowledge Representation and Reasoning
- CSC2503H – Foundations of Computer Vision
- CSC2511H – Natural Language Computing
- CSC2515H – Introduction to Machine Learning (exclusion: ECE1513H)
- CSC2516H – Neural Networks and Deep Learning (exclusion: MIE1517H)
- CSC2529H – Computational Imaging
- CSC2533H – Foundations of Knowledge Representation
- CSC2630H – Introduction to Mobile Robotics
- ECE1512H – Digital Image Processing and Applications
- ECE1513H – Introduction to Machine Learning (exclusion: CSC2515H)
- MAT1510H – Deep Learning: Theory and Data Science
- MIE1517H – Introduction to Deep Learning (exclusion: CSC2516H)
