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Module Title Neural Computation
SchoolComputer Science
Department Computer Science
Module Code 06 20416
Module Lead Dr R Bahsoon
Level Honours Level
Credits 10
Semester Semester 1
Pre-requisites
Co-requisites
Restrictions As given in the programme specifications for School of Computer Science programmes.
Pre-requisite of A-Level Maths or equivalent.
May not be taken by anyone who has taken or is taking Introduction to Neural Computation.
Contact Hours Lecture-23 hours
Total: 23 hours
Exclusions
Description The module introduces the basic concepts and techniques of neural computation and, more generally, automated learning in computing machines. It covers various forms of formal neurons and their relation to neurobiology, showing how to construct larger networks of formal neurons and study their learning and generalisation in the context of practical applications. Finally, neural-based learning techniques are contrasted with other state-of-the-art techniques of automated learning.
Learning Outcomes By the end of the module the student is expected to be able to:
  • Understand the relationship between real brains and simple artificial neural network models;
  • Describe and explain some of the principal architectures and learning algorithms of neural computation;
  • Explain the learning and generalisation aspects of neural computation;
  • Demonstrate an understanding of the benefits and limitations of neural-based learning techniques in context of other stateof-the-art methods of automated learning.
Assessment 20416-01 : Examination : Exam (Centrally Timetabled) - Written Unseen (80%)
20416-03 : Continuous Assessment : Coursework (20%)
Assessment Methods & Exceptions 1.5 hr examination (100%)
Other None
Reading List