MSc Artificial Intelligence

• Programme overview

• 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

  COMP5008
  Advanced Machine Learning 20 credits

  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.

  100% Coursework

  PROJ518
  MSc Dissertation and Research Skills 60 credits

  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.

  100% Coursework

  COMP5012
  Computational Intelligence 20 credits

  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.

  100% Coursework

  ROCO507Z
  Advanced Robot Design and Prototyping 20 credits

  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.

  70% Coursework

  30% Examinations

  PROJ519
  MSc Dissertation and Research Skills 60 credits

  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.

  100% Coursework

  COMP5019
  Natural Language Processing and Large Language Models 20 credits

  This module introduces the foundational concepts and applications of Natural Language Processing (NLP) and Large Language Models (LLMs). It covers the theoretical underpinnings of language processing techniques and provides experience in developing and fine-tuning LLM models. Students will learn how NLP and LLMs, such as BERT and GPT, are utilized in diverse domains enabling them to tackle complex challenges effectively.

  100% Coursework

  MATH517
  Big Data Visualisation and Analytics 20 credits

  Sophisticated techniques are needed to visualize and analyse increasing quantities of Big Data. This module introduces the modern data science techniques and professional software to handle large complex datasets, as well as experience of writing professionally documented code and data analysis reports. Data analysis pipelines, including data cleansing, are used to produce data visualizations and statistical analysis.

  100% Coursework

  ROCO510
  Computer Vision and Deep Learning 20 credits

  This module will provide an advanced knowledge of computer vision systems for autonomous robots. It will be underpinned by current theoretical understanding of animal vision systems, feature detection/recognition, and stereo vision/calibration. This module will also introduce the use of deep-learning neural networks (deep feedforward, convolutional, and recurrent) in vision systems.

  50% Coursework

  50% Examinations

  Optional modules

  COMP5011
  Cyber-Physical Systems Security 20 credits

  This module looks at developing the necessary skills and techniques for analysing, critiquing and designing secure cyber-physical systems (CPS). Examples of CPS include the Internet of Things, transportation, robotics, maritime shipping and autonomous vehicles. Consideration is given to a systems-based approach to the security analysis of CPSs, the identification of vulnerabilities and the development of secure solutions.

  100% Coursework

  COMP5018
  Human-Robot Interaction 20 credits

  This module provides comprehensive knowledge of (social and cognitive) human-robot interaction, emphasizing the development of interactive robot systems for real-world applications. It further investigates the mechanisms by which intelligent robots assimilate and adapt to their environments, along with methodologies that govern their actions in dynamic contexts.

  100% Coursework

  MATH516
  Machine Learning and Artificial Intelligence for Healthcare 20 credits

  This module aims to introduce the cutting-edge techniques in machine learning and artificial intelligence for health data analytics. The practical implementation will be achieved using appropriate software.

  100% Coursework

MSc Artificial Intelligence programme specification_7045

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.

Most of our taught programmes begin in September. Applications can usually be made throughout the year, and are considered until programmes are full.

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Support is also available to overseas students applying to the University from our International Office. Take a look at our how to apply information or email admissions@plymouth.ac.uk.

Once you are happy that you have all of the information required you can apply using our online postgraduate application form (the blue 'Apply' icon on this page).

You will normally receive a decision on your application within four weeks of us receiving your application. You may be asked to provide additional information; two academic/professional references, confirming your suitability for the course; or to take part in an interview (which in the case of overseas students may be by telephone or video conference) and you will be sent a decision by letter or email.

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More information and advice for applicants can be referenced in our admissions policy which can be found on the student regulations, policies and procedures page. Prospective students are advised to read the policy before making an application to the University.