Module 32212 (2022)

Module description - Neural Computation (Extended)

The Module Description is a strict subset of the Syllabus Page.

Module Title	Neural Computation (Extended)
School	School of Computer Science
Module Code	06-32212
Level	4/M
Member of Staff	Jinming Duan Konstantinos Kamnitsas Yunwen Lei
Semester	Semester 1 - 20 credits
Description	This course focuses on artificial neural networks and their use in machine learning. It covers the fundamental underlying theory, as well as methodologies for constructing modern deep neural networks, which nowadays have practical applications in a variety of industrial and research domains. The course also provides practical experience of designing and implementing a neural network for a real-world application.
Outcomes	On successful completion of this module, the student should be able to: Describe and explain some of the principal architectures and learning algorithms of neural computation Explain the learning and generalisation aspects of neural computation networks Demonstrate an understanding of the benefits and limitations of neural networks in comparison to other machine learning methods. Develop and apply neural network models to specific technical and scientific problems
Assessment	Main Assessments: Examination (80%) and continuous assessment via coursework (20%) Supplementary Assessments: Examination (100%)