The Robotics programme is the bridge between a personal interest in the world of Robotics and Artificial Intelligence and a top-level professional future in one of the most exciting and fast growing fields of technology.

The programme offers theoretical and practical knowledge in robotics, including: manipulators control, computer vision, sensors, machine learning, grasping, robotic hands. It also offers the opportunity to develop robots and robotic devices for current and future industry uses.

Modern robotics has assumed a large part of our daily lives, be it through prosthetics, industrial automatisation, or even household cleaning. Throughout this course, the curriculum will put emphasis on emerging technological advancements in this exciting field, culminating in work/study experience that will set you on the path towards a meaningful and fulfilling career in this ever evolving field.

For admission, some prerequisites are required - namely a bachelor's or master's degree in Robotics, Data Science, Computer Science, Electrical or Mechanical Engineering, or related disciplines. We welcome motivated individuals - technology enthusiasts who can work effectively both in teams as well as in isolation, who have the humility and the passion to learn when they don’t know, and who have the drive to step up and lead when it is asked of them.






Matrix operations; import/export of data; plotting

ROS - Optional


Linear Algebra (Inversion, Eigenvalues, Null-Space)

Linear Differential Equations

Basic Calculus

Numerical Integration (Basic Computational Implementation)


Mechanics (Forces, torques, mass / inertia, Equations of motion)

Control Theory

Controls Fundamentals


Basic experience with circuits (elements, interactions, PCBs)


Basic design and fabrication experience


1. Advanced Algorithms & Data Structures

2. Theory Of Probability And Statistics

3. Discrete Optimisation

4. Mechatronics Design

5. Integrated Intelligence In Robotics:

Vision, Language, And Planning

6. Machine Learning

7. Dynamic Optimisation

8. Computer Vision

9. Neural Networks And Deep Learning

10. Industrial Machine Learning

11. Kinematics, Dynamics And Control

12. Manipulation, Estimation And Control

13. Hands: Design And Control For Dexterous Manipulation

14. Manipulation Algorithms

15. Reinforcement Learning In Robotics

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Last updated January 21, 2019
This course is Campus based
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