The proposed graduate programme is interdisciplinary, combining topics from Computer Science and Computer Engineering. The programme requires 30 credit-hours (or 10 courses of 3 credit-hours each). From those, 21 credit-hours (or seven 3-credit-hour courses) are core courses and 9 credit-hours (or three 3-credit-hour courses) are from elective courses, either from the list below or an approved replacement.

The core courses are:

• AI 6000 - Artificial Intelligence Foundations
• AI 6001 - Topics in Artificial Intelligence
• AI 6002 - Artificial Intelligence Capstone1
• COMP 6901 - Applied Algorithms
• COMP 6915 - Introduction to Machine Learning
• COMP 6980 - Algorithmic Techniques for Artificial Intelligence
• ENGI 9818 - Software Fundamentals

The elective courses are:

• COMP 6907 Data Mining Techniques and Methodologies
• COMP 6912 Autonomous Robotics
• COMP 6934 Introduction to Data Visualization
• COMP 6981 Data preparation techniques
• COMP 6936 Advanced Machine Learning
• DSCI 6601 Practical Machine Learning
• DSCI 6602 Deep Learning and Artificial Intelligence or MATH 6205 Deep Learning
• ENGI 9804 Image Processing and Applications
• ENGI 9805 Computer Vision or COMP 6982 Computer Vision
• ENGI 9821 Digital Signal Processing
• ENGI 9826 Advanced Control Systems
• ENGI 9940 Advanced Robotics

Please note that not all elective courses are offered every year. They may be offered every other year.

Schedule

The first term is preparatory in nature, covering key aspects from mathematics and computing that will be required for subsequent courses. The second term provides a broad introduction to Artificial Intelligence. The third and fourth terms focus on electives and a capstone course, allowing students to begin to specialize in their topics of interest.