The aims of this module are to:

• enhance awareness and critical appreciation of high-quality research-based publications;
• develop ability to communicate research-findings to others in an independent minded manner;
• develop skills in research methods.

The aim of this module is to provide an up-to-date introduction to state-of-art artificial intelligence with a particular focus on the developments of the last five to ten years. The module will introduce specific methods within the scientific contexts in which AI has seen considerable progress. The module will also prepare students for the in-depth analysis of the various methods presented in the following modules in the programme.

This module aims to prepare students to apply modern machine learning techniques to solve various real-world challenges as well as exploring state-of-the- art deep learning technology. This self-contained module will introduce conventional machine learning methods and new deep neural network development. With the understanding of the techniques, the students will gain the ability to apply and develop practical machine learning solutions for real-world applications, thus to satisfy industrial needs under different scenarios.

The aims of this module are to provide students with the relevant concepts of robotics from the AI perspective and the skills for developing planning and learning systems that apply to robotics.

The main aim of this module is to introduce students to computer-based understanding, analysis and processing of images taken with a digital camera. The module introduces various methods and algorithms that allow computers to store images, process images (e.g. enhance images), extract useful information from images, classify images, and organise image collections. The module also aims to specify and discuss the problems of image understanding and of various computer vision applications.

This module aims to introduce key concepts in Natural Language Processing (NLP), a field of using statistical methods and machine learning algorithms for processing written natural language. The module will equip students with a fundamental understanding of methods for processing linguistic data in textual form, associated challenges, and applications. The module will also provide students with the practical skills to analyse textual data using fundamental and state-of-the-art NLP methods.

The aim of this module is to introduce the student to distributed AI systems through the notion of an agent, how it can be constructed, and how multiple agents can be made to cooperate effectively with one another to solve complex AI problems.

The aims of this module are to:

• Introduce the facets of research from broad research philosophy to detailed data collection.
• Develop critical analysis skills across a range of different sources.
• Introduce ethical thinking into the development of an appropriate research methodology.

The aim of this module is to allow students to demonstrate their analysis, design and programming skills, acquired in previous modules of their MSc, by applying what they have learned to a substantial problem in Artificial Intelligence. The project must be related to their MSc studies and the student should be able to show they can apply the latest research and developments in their project.