Key features
- The programme has the potential for students to tailor their degree towards the industry in which they wish to apply their AI knowledge by selecting and exploring industry-relevant data sets and problems.
- A combination of module types, including technical modules facilitating a deep-dive of cutting-edge AI technologies and providing experience of constructing AI software from first principles, alongside workshop modules providing insight into the field of AI as a whole. Each Semester is comprised of two technical modules and a workshop module.
- An embedded research-informed teaching experience offering state-of-the-art knowledge, skills and practice, delivered by internationally recognised and world-leading academics. Students will work directly with these academics, receiving education, support and guidance from researchers at the forefront of AI research.
- Excellent facilities for conducting research and project work in AI and robotics, including a range of state-of-the-art robotics laboratories, recently-updated computing facilities and the new engineering design facility, all of which provide an inclusive learning environment.
- The programme incorporates a substantial element of practical and production-based work, resulting in an end product of industrial quality that solves a relevant problem. The programme’s assessment is inclusive, being completely coursework and practice based, and providing authentic and holistic means of assessing progress.
- We promote learning through practice and doing, and a prominent feature of the programme is a dissertation module that enables students to draw together the rest of their taught content to produce outputs of a professional and publishable standard.
- As a result of our industrial links students have excellent employment opportunities with a wide variety of organisations. These include both providers and consumers of AI.
Course details
Year 1
- Students will learn a variety of cutting edge AI topics including machine learning, computational intelligence, computer vision and robotics. In all modules there is a focus on industrial problem solving with AI, and you will complete a dissertation in which you will conduct a deep exploration of a topic of your choice. Throughout your studies you will gain practical experience of constructing AI using both existing tools and innovating new methods from first-principles.
Core modules
Artificial Vision and Deep Learning (AINT515)
This module will provide an advanced knowledge of artificial vision systems for autonomous robots. It will be underpinned by current theoretical understanding of animal vision systems and computational models. This module will introduce the use of deep-learning neural networks in vision systems.
Advanced Machine Learning (COMP5008)
This module equips students with knowledge of the underlying theory of machine learning, as well as practical skills that enable them to apply theory to real-world problems. A variety of problems (including unsupervised, supervised and reinforcement learning tasks) are considered with a range of cutting-edge techniques. Students can customise the module to their career aims by identifying and exploring relevant data sets.
Big Data and Social Network Visualization (MATH513)
Sophisticated analytics techniques are needed to visualize today's increasing quantities of Big Data. Up-to-date R tools including dplyr for data manipulation, ggplot2 for visualization, and knitr/LaTeX for document presentation are studied. These are applied to database interrogation, social network visualization and sentiment analysis. The module provides considerable experience of writing professionally documented R code using RStudio.
MSc Dissertation and Research Skills (PROJ518)
You will develop a methodical approach to research that helps propose research projects that are practically realistic and academically worthwhile. A substantial project will be planned and carried out using ethically suitable quantitative and qualitative research methods. The project will be reported through a high quality, scholarly and professional write-up, either as a formal dissertation or journal paper.
Computational Intelligence (COMP5012)
This module examines the state-of-the-art in computational intelligence, focussing on evolutionary computation, swarm intelligence, fuzzy systems and Bayesian and Markov networks. Students will learn about the underlying theory behind these techniques and gain practical experience of implementing them. CI approaches will be discussed against the backdrop of various industrial problems that they are suited to solving.
Topics in Applied Artificial Intelligence (COMP5013)
This module provides students with a view of how artificial intelligence is used within research and commercial settings. Delivered by a mix of academics developing novel AI techniques, and research and commercial users of AI, the module will enable students to appreciate the range of complexities inherent in the application of AI to solving real-world problems. As well as technical topics, the ethics of AI are explored.
Advanced Robot Design and Prototyping (ROCO507Z)
This module aims to give the students a theoretical and practical understanding of designing and building advanced robot assemblies and mechanisms, through engineering and bioinspired approaches.
MSc Dissertation and Research Skills (PROJ519)
You will develop a methodical approach to research that helps propose research projects that are practically realistic and academically worthwhile. A substantial project will be planned and carried out using ethically suitable quantitative and qualitative research methods. The project will be reported through a high quality, scholarly and professional write-up, either as a formal dissertation or journal paper.
Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.
The following programme specification represents the latest programme structure and may be subject to change:
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