Prerequisite:
1. IRE 205: IoT Architecture and Technologies
2. IRE 305: Robotics Dynamics and Kinematics
3. IRE 307: System Engineering and Testing
4. IRE 313: Sensor Technology
5. IRE 317: Control System Engineering
Core Courses:
1. IRE 501: Systems Dynamics and Modelling
2. IRE 502: Mechatronics System Design
3. IRE 503: Natural Language Processing
4. IRE 520: Microsystem Technology
5. IRE 521: Sensor Based Systems and Design
6. IRE 522: Multivariable Adaptive Control System
7. IRE 523: Robot Manipulation and Mobility
8. IRE 524: Robot Perception and Vision
9. IRE 525: Physics of Living Systems
10. IRE 560: Cognitive and Collaborative Robots
11. IRE 561: Medical Robotics and Surgical Techniques
12. IRE 564: Computational and Learning Social Robots
13. IRE 565: Autonomous driving
14. IRE 580: Brain Machine Interfaces
15. IRE 581: Reinforcement Learning
16. IRE 582: Optimal Control Theories and Applications
17. IRE 583: Distributed Machine Learning
18. IRE 584: Deep Reinforcement Learning
19. IRE 585: Intelligent Networks for Machines
20. IRE 586: Augmented and Virtual Reality
21. IRE 587: Cognitive Neural Engineering
(Basic 01, IoT Design 20, Communication 40, Robotics 60, Learning and Management 80)
IRE 500E: Project and Thesis (M. Eng.)
IRE 500S: Project and Thesis (M. Sc.)
IRE 600: Project and Thesis (PhD)
Degree Requirements:
Master of Science (M. Sc.) in IoT and Robotics:
6 (core courses) x 3 + 18 (Thesis) = 36 Credits
Master of Engineering (M. Eng.) in IoT and Robotics:
10 (core courses) x 3 + 6 (Thesis) = 36 Credits
PhD in IoT and Robotics:
3 (Core Courses) x 3 + 45 (Thesis) = 54 Credits