Traditional lectures are used to convey knowledge from teacher to student, and students are actively encouraged to engage in discussion during class. During the practical sessions, students will undertake various laboratory exercises implementing and exploring a variety of algorithms. Group learning is also utilised via a module group project and also a cross-module group project as possible. A term paper will involve a more in-depth study of the topics raised.
Module Aim:
To immerse students in the formal theory, and the application of contemporary techniques in Machine Learning for computer games development.
Learning Outcomes
On successful completion of this module the learner should be able to:
LO1
Demonstrate an excellent understanding of non symbolic approaches to Artificial Intelligence
LO2
Understand, evaluate and communicate the key principles, theories and techniques specific to the training of Machine Learning models.
LO3
Apply key principles, theories and techniques (particularly Machine Learning technologies) with respect to computer games development.
Pre-requisite learning
Module Recommendations
This is prior learning (or a practical skill) that is recommended before enrolment in this module.
No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed.