| Module code | EAI 732 |
| Qualification | Postgraduate |
| Faculty | Faculty of Engineering, Built Environment and Information Technology |
| Module content | This module provides the theoretical background necessary to understand, research and develop real-world software and hardware systems that incorporate and exhibit intelligent behaviour. The module incorporates advanced theory from fields such as Artificial Intelligence, Computational Intelligence, Machine Learning, Pattern Recognition and Signal Processing. Core topics of the module include: Bayesian Theory, Neural Networks, Kernel Methods, Graphic Models, and Numerical Bayesian Methods. |
| Module credits | 32.00 |
| Programmes | |
| Prerequisites | No prerequisites. |
| Contact time | 10 lectures per week |
| Language of tuition | Module is presented in English |
| Academic organisation | Electrical, Electronic and Com |
| Period of presentation | Semester 1 |
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