Masters.

Core algorithms and data structures, combined with relational and non-relational database theory.

Data and information visualisation — perception, design principles, and interactive visual analytics.

Algorithmic techniques for large-scale data: streaming, sketching, sampling and optimisation.

Trajectory planning, control theory and autonomous navigation for robotic systems.

Security engineering — threat modelling, secure design principles and security management.

The mathematical underpinnings of AI — linear algebra, probability, optimisation and information theory.

Data manipulation, statistical programming, and analysis pipelines for data science applications.

Core AI techniques and machine learning — from probabilistic models to deep learning.

Digital forensics techniques, malware analysis and structured penetration testing methodology.

Advanced database systems — storage engines, distributed data, big data processing and cloud data management.

Cryptographic primitives, protocol design and network-level security attacks and defences.

Advanced computer architecture, compilers, operating systems and low-level systems programming.

Cutting-edge topics across artificial intelligence and data science, covering recent research and emerging methods.

Computer vision techniques applied to robotic perception — feature detection, stereo vision and SLAM.

Motion planning, kinematics, sensor fusion and autonomous robot systems.