Artificial Intelligence (AI) and Machine Learning (ML) have exploded in importance in recent years and garnered attention in a wide variety of application areas, including computer vision (e.g., image recognition), game playing (e.g., AlphaGo), autonomous driving, speech recognition, customer preference elicitation, bioinformatics (e.g. gene analysis) and others.
While the topics may appear primarily to reside in the disciplines of computer engineering and computer science, the topics of AI and ML now apply to all disciplines of engineering, such as the projection of future road-traffic patterns, applications in industrial automation and robotic control, or the use of AI/ML drug discovery, to name just a few examples.
All U of T Engineering undergraduates (except students in the Engineering Science Machine Intelligence and Robotics majors) are eligible to participate in this certificate.
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Requirements
The requirements for the Certificate in Artificial Intelligence Engineering in the Faculty of Applied Science and Engineering are the successful completion of the following courses:
- APS 360H1: Applied Fundamentals of Deep Learning
- One of:
- ECE 345H1: Algorithms & Data Structures
- ECE 358H1: Foundations of Computing
- CSC 263H1: Data Structures & Analysis
- MIE 335H1: Algorithms & Numerical Methods
- MIE245H1: Data Structures & Algorithms
- One of:
- ROB 311H1: Artificial Intelligence
- CSC 384H1: Introduction to Artificial Intelligence
- ECE 421H1: Introduction to Machine Learning
- CSC 311H1: Introduction to Machine Learning (formerly CSC 411)
- ROB 313H1: Introduction to Learning From Data
- MIE 424H1: Optimization in Machine Learning
- MIE 369H1: Introduction to Artificial Intelligence
Notes
Availability of the courses (including the foundation courses) for timetabling purposes is not guaranteed; the onus is on the student to ensure compatibility with their timetable.
Students must secure approval from their home department before selecting any elective outside their departmental approved list.