MSc Artificial Intelligence

at University of Plymouth

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.
 

Topics in Advanced Intelligent Robotics (AINT516)
This module introduces the research activities of the Centre for Robotics and Neural Systems (CRNS). It is taught by CRNS members who lead thematic workshops on their own areas of expertise, such as swarm robotics, cognitive robotics, Human-Robot Interaction, and bio-inspired cognitive architectures. The module also covers scientific research methods and data analysis.
 

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.

A lower second class (2:2) honours degree or better in a STEM-based discipline. Applicants will need to have a sound awareness of programming and be comfortable in learning programming techniques. Applicants without any prior programming experience may be accepted subject to undertaking preparatory work prior to the start of the programme. Applicants with a lower classification, or substantial industrial experience in lieu of formal qualifications may be considered subject to interview.
 

A minimum IELTS English proficiency score of 6.5, with at least 5.5 in each component. 
 

The programme adheres to the University regulations and guidelines for the Accreditation of Prior Experiential Learning (APEL) and Accreditation of Prior Certificated Learning (APCL) for Masters programmes. 
 

Students are required to produce evidence of English language ability. This will normally be the equivalent of GCSE Grade C or above in English language or IELTS average score of 6.5 or above with at least 6.0 in the written component.

International - £16,700