Education

Artificial intelligence and data-driven systems

• Deep learning for visual recognition, including convolutional networks, attention mechanisms, and Transformers.
• Generative AI, including VAEs, GANs, diffusion models, and predictive coding.
• Reinforcement learning, probabilistic reasoning, optimisation, and intelligent decision-making.
• Data engineering, feature processing, model validation, monitoring, fairness, transparency, and explainability.

Robotics, autonomous systems, and interaction

• Autonomous vehicle architectures, perception, sensor fusion, localisation, mapping, and SLAM.
• Robot control, dynamic systems, neural fields, reactive navigation, and multi-agent systems.
• Simulation and programming of mobile robots, collective robotics, and intelligent agents.
• Human-Computer Interaction, user-centred design, information visualisation, virtual and augmented reality, and multimodal interfaces.
• Parallel programming for high-performance and distributed intelligent systems.

Visual computing

• Image and signal processing, including filtering, segmentation, morphology, feature extraction, and image matching.
• Deep learning for computer vision, object detection, self-supervised representations, and multimodal learning.
• Applications in 3D reconstruction, biomedical imaging, remote sensing, image retrieval, and pattern recognition.

Computer science and artificial intelligence

• Machine learning, neural networks, Bayesian inference, optimisation, data mining, and large-scale data management.
• Knowledge representation, logic, computational argumentation, and automated planning for explainable intelligent systems.
• Practical development with Python, scientific libraries, web technologies, APIs, databases, and cloud-native deployment.

Visual computing

• Visualisation of large, spatial, geospatial and graph-based data.
• Computer graphics, 3D modelling, lighting and procedural generation.
• Image and video analysis for enhancement, segmentation, recognition and motion interpretation.
• Computer vision: SIFT features, camera calibration, stereo vision and 3D reconstruction.
• Virtual/augmented reality, interactive environments and video-game development.
• Mobile multimedia applications and image, audio and video compression.

Computer science and artificial intelligence

• Advanced algorithms and complexity, operating systems, networks, distributed systems and databases.
• Problem solving, knowledge representation, modal logic and game theory.
• Machine learning, neural networks, SVMs, data mining and multivariate data analysis.
• Compilation, code optimisation and project management.

Program focus

• Core computer science foundations: algorithms, computer architecture, operating systems, and networks.
• Fundamental methods including logic, graph theory, numerical analysis, probability, and statistics.
• Software development and testing.
• Organizational structures and their management, information, and operational systems.
• The complete information-system development lifecycle, from requirements analysis to implementation, using modern design methods, software-development techniques, and databases.