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Core modules:

Text Processing

This module introduces fundamental concepts and ideas in natural language text processing, covers techniques for handling text corpora, and examines representative systems that require the automated processing of large volumes of text. The module focuses on modern quantitative techniques for text analysis and explores important models for representing and acquiring information from texts. You should be aware that there are limited places available on this course. 

15 credits

Speech Processing

This module aims to demonstrate why computer speech processing is an important and difficult problem, to investigate the representation of speech in the articulatory, acoustic and auditory domains, and to illustrate computational approaches to speech parameter extraction. It examines both the production and perception of speech, taking a multi-disciplinary approach (drawing on linguistics, phonetics, psychoacoustics, etc.). It introduces sufficient digital signal processing (linear systems theory, Fourier transforms) to motivate speech parameter extraction techniques (e.g. pitch and formant tracking). You should be aware that there are limited places available on this course. 

15 credits

Machine Learning and Adaptive Intelligence

The module is about core technologies underpinning modern artificial intelligence. The module will introduce statistical machine learning and probabilistic modelling and their application to describing real-world phenomena. The module will give students a grounding in modern state-of-the-art algorithms that allow modern computer systems to learn from data. It has a considerable focus on the mathematical underpinnings of key ML approaches, requiring some knowledge of linear algebra, differentiation and probability.

Students should be aware that there are limited places available on this module.

15 credits

Professional Issues

This module aims to enable students to recognise the legal, social, ethical and professional issues involved in the exploitation of computer technology and be guided by the adoption of appropriate professional, ethical and legal practices. It describes the relationship between technological change, society and the law, including the powerful role that computers and computer professionals play in a technological society. It introduces key legal areas which are specific and relevant to the discipline of computing (e.g., intellectual property, liability for defective software, computer misuse, etc) and aims to provide an understanding of ethical and societal concepts that are important to computer professionals, and experience of considering ethical dilemmas.

15 credits

Scalable Machine Learning

This module will focus on technologies and algorithms that can be applied to data at a very large scale (e.g. population level). From a theoretical perspective it will focus on parallelisation of algorithms and algorithmic approaches such as stochastic gradient descent. There will also be a significant practical element to the module that will focus on approaches to deploying scalable ML in practice such as SPARK, programming languages such as Python/Scala and deployment on high performance computing platforms/clusters.

15 credits

Team Software Project

This team project aims to provide insights and wider context for the more practical aspects of the taught modules, and to provide students with experience of working in teams to develop a substantial piece of software.

15 credits

Speech Technology

This module introduces the principles of the emergent field of speech technology, studies typical applications of these principles and assesses the state of the art in this area. You will learn the prevailing techniques of automatic speech recognition (based on statistical modelling); will see how speech synthesis and text-to-speech methods are deployed in spoken language systems; and will discuss the current limitations of such devices. The module will include project work involving the implementation and assessment of a speech technology device. You should be aware that there are limited places available on this module.

15 credits

Natural Language Processing

This module provides an introduction to the field of computer processing of written natural language, known as Natural Language Processing (NLP). We will cover standard theories, models and algorithms, discuss competing solutions to problems, describe example systems and applications, and highlight areas of open research. You should be aware that there are limited places available on this module.

15 credits

Dissertation Project

For your individual project, you can choose from a wide range of possibilities in many different environments both within and outside the University. The project is completed during the summer, and you will have a personal academic supervisor to guide you during this period.

60 credits