The indicative content for this module includes the study of fundamental pattern recognition in relation to supervised learning. Topics will include Bayesian decision theory, Artificial Neural Networks and Support Vector Machines (amongst others). The nature of these algorithms will be studied along with engineering techniques for developing smart applications. Further, deep learning for engineering applications (e.g. classification of electrocardiograms) will be studied. Finally, students will undertake a coursework to apply an appropriate machine learning methodology to solve a real-world pattern recognition problem.