The extent to which Artificial Intelligence (AI) is now ingrained in science/technology development and increasingly central to everyday life is captured in the report and mission of the international One Hundred Year Study on Artificial Intelligence (September 2016). AI advances strive to achieve, to ever-greater degrees of efficacy, reliability and safety, the ways in which machines and systems perceive, see, speak, decide, respond, act and plan. AI questions engage investigators across a range of disciplines—from the computer, statistical and actuarial sciences; to electrical/computer, mechatronics and systems design; to combinatorics and optimization; cognitive science; psychology; biology; applied health science; economics; political science; and law; among others.
The AI Option is available for both the Bachelor of Computer Science (BCS) and the Bachelor of Mathematics (BMath) Computer Science plans. Students in BCS Data Science are not eligible for this option. The requirements are the same as for the BCS and BMath Computer Science (CS) plans with the following constraints on upper-year CS courses:
All of
CS 486 Introduction to Artificial Intelligence
CS 492 The Social Implications of Computing
One of
CS 480 Introduction to Machine Learning
CS 485 Statistical and Computational Foundations of Machine Learning
One of
ECE 380 Analog Control Systems
SE 380 Introduction to Feedback Control
Three additional courses from
CO 367 Nonlinear Optimization
CO 456 Introduction to Game Theory
CO 463 Convex Optimization and Analysis
CO 466 Continuous Optimization
CS 452 Real-time Programming
CS 480 Introduction to Machine Learning
CS 484 Computational Vision
CS 485 Statistical and Computational Foundations of Machine Learning
STAT 341 Computational Statistics and Data Analysis
STAT 440 Computational Inference
STAT 441 Statistical Learning - Classification
STAT 444 Statistical Learning - Function Estimation
ECE 423 Embedded Computer Systems
ECE 481 Digital Control Systems
ECE 486 Robot Dynamics and Control
ECE 488 Multivariable Control Systems
MSCI 446 Data Warehousing and Mining
MTE 544 Autonomous Mobile Robots
SYDE 372 Introduction to Pattern Recognition
SYDE 522 Machine Intelligence
SYDE 556 Simulating Neurobiological Systems
Note: At least one of the “Three additional courses” must be from Math and at least one from Engineering.
Special topics courses (e.g., CS 489) may sometimes be appropriate for this option; interested students should see the option co-ordinator for confirmation.