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 computer and statistical sciences; to electrical and systems design engineering; to optimization; cognitive science; applied health sciences; economics; and law, among others.
The AI Option is available for students in all undergraduate engineering plans at the University of Waterloo. The requirements for option completion are:
All of
ECE 457A Cooperative and Adaptive Algorithms, or MSCI 435 Advanced Optimization Techniques
MSCI 442 Impact of Information Systems on Organizations and Society
One of
CS 480 Introduction to Machine Learning
ECE 457B Fundamentals of Computational Intelligence
MSCI 446 Data Mining
One of
BME 356 Control Systems
CHE 420 Introduction to Process Control
ECE 380 Analog Control Systems
MTE 360 Automatic Control Systems
SE 380 Introduction to Feedback Control
SYDE 352 Introduction to Control Systems
Three additional courses from
CHE 522 Advanced Process Dynamics and Control
CHE 524 Process Control Laboratory
CO 456 Introduction to Game Theory
CO 463 Convex Optimization and Analysis
CO 466 Continuous Optimization
CS 480 Introduction to Machine Learning
CS 484 Computational Vision
CS 485 Statistical and Computational Foundations of Machine Learning
ECE 423 Embedded Computer Systems
ECE 455 Embedded Software
ECE 481 Digital Control Systems
ECE 486 Robot Dynamics and Control
ECE 488 Multivariable Control Systems
MSCI 446 Data Mining
MTE 544 Autonomous Mobile Robots
STAT 341 Computational Statistics and Data Analysis
STAT 440 Computational Inference
STAT 441 Statistical Learning - Classification
STAT 444 Statistical Learning - Function Estimation
SYDE 522 Machine Intelligence
SYDE 556 Simulating Neurobiological Systems
SYDE 572 Introduction to Pattern Recognition
Note: At least one of the “Three additional courses” must be from Mathematics and at least one from Engineering. Special topics courses may sometimes be appropriate for this Option; interested students should see the option co-ordinator for confirmation.