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 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 undergraduate Engineering students are eligible to participate in this certificate except students in the Engineering Science Machine Intelligence Major and the Robotics Major.
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:
|APS360H1: Artificial Intelligence Fundamentals||S||3||-||1||0.50|
|ECE345H1: Algorithms and Data Structures||F/S||3||-||2||0.50|
|ECE358H1: Foundations of Computing||F||3||-||1||0.50|
|MIE335H1: Algorithms & Numerical Methods||S||3||1||1||0.50|
|ROB311H1: Artificial Intelligence||S||3||-||1||0.50|
|ECE421H1: Introduction to Machine Learning||S||3||-||2||0.50|
|CSC311H1: Introduction to Machine Learning||S||2||-||1||0.50|
|MIE369H1: Introduction to Artificial Intelligence||S||3||-||2||0.50|
|MIE424H1: Optimization in Machine Learning||S||-||-||-||0.00|
|ROB313H1: Introduction to Learning from Data||S||3||-||2||0.50|
Engineering Science students enrolled in the Robotics Major are not eligible for the AI Engineering Certificate due to overlapping core course requirements.