Module aim is to introduce the student to the main computational models of neurons, from the simplest sum-and-threshold units through to detailed compartmental models, and understand the relevance and applicability of the various models to computational problems. The student will learn about training paradigms for artificial neuron networks and how this relates to learning in biological networks. The aim is to equip the student to use artificial neural networks appropriately to solve a wide range of problems, and to provide the some of the fundamental ideas from neuroscience that will allow the student to undertake further study of neural networks.
Module learning outcomes
On completion of this module, students will:
Understand neuron models (artificial and biologically motivated) (assessed in closed exam)
Be able to create neural networks with appropriate architectures (assessed in open exam)
Understand and be able to apply learning and training algorithms (assessed in open and closed exam)
Apply neural networks to real problems (assessed in open exam)
Understand the analysis of performance of neural networks (assessed in open and closed exam)
Academic and graduate skills On completion of this module, students will have:
Developed their written communication skills (assessed in report on practical assessment)
Developed their analysis and problem solving skills (assessed in report on practical assessment)
Developed their academic reading skills (assessed in depth of closed exam answers)
% of module mark
Practical Programming Exercise
University - closed examination Introduction to Neural Computing & Applications (INCA)
Special assessment rules
% of module mark
University - closed examination Introduction to Neural Computing & Applications Reassessment Exam
Feedback to students will be available via:
Verbal feedback on practical sessions.
Model or outline solutions to exercises, usually 2 weeks after related lab sessions, for self-evaluation.
Feedback on practical assessment within 4 term weeks of submission.
Feedback on closed examination within 4 terms weeks of examination, and before end of academic year.