Brayford Pool
September 2025 and January 2026
1 year
2 years
The MSc Artificial Intelligence is designed to equip students with the advanced knowledge and skills needed to develop the innovative solutions required by the emerging global AI Vision industry in healthcare, brain sciences, medical imaging, robotics, manufacturing, retail, agriculture, space, energy, and nuclear.
Course content is informed by research carried out in the School of Computer Science, especially in brain-inspired AI, deep learning, machine learning, data analytics, computer vision, and neurobotics. This approach aims to ensure content is both leading-edge and underpinned by the latest thinking in the field.
The programme provides students the chance to enhance and apply existing knowledge of computer programming and mathematical frameworks through laboratory workshops, lectures, debates, and independent research. The course assumes a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain.
Students also have the opportunity to undertake a substantial research project focusing on an area of personal and professional interest, through the development of a dissertation and substantive software implementation.
A focus on advanced knowledge and skills to develop the innovative solutions
Informed by the research of academic teams at Lincoln
Taught by academics with specialist experience in relevant areas
Complete an independent research project in a specialist area
Students on this programme can experience a blend of different teaching and learning approaches. The programme aims to enable the development of skills through practical workshops in the laboratory, and academic knowledge through debate, lectures, discussion, and personal research.
Modules assume a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain. Each module typically consists of 12 weeks of study. This time includes a supporting lecture programme, a series of supported laboratory sessions, and time for the completion of assignment exercises and examinations. Weekly contact hours on this programme may vary depending on the individual module options chosen and the stage of study. The programme is also supported by online access to lecture material and related information.
Postgraduate level study involves a significant proportion of independent study, exploring the material covered in lectures and seminars. As a general guide, for every hour spent in class, students are expected to spend at least two to three hours in independent study.
Students must complete a substantial research project focusing on an area of personal and professional interest, for example through a substantive software implementation and the development of a dissertation.
This module aims to cover the theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents.
Search is introduced as a unifying framework for Artificial Intelligence (AI), followed by key topics including blind and informed search algorithms, planning and reasoning, both with certain and uncertain (e.g. probabilistic) knowledge. Practical exercises in AI programming will complement and apply the theoretical knowledge acquired to real-world problems.
This module aims to cover the theoretical fundamentals and practical application of machine learning algorithms, including supervised, unsupervised, reinforcement and evolutionary learning. Practical programming exercises complement and apply the theoretical knowledge acquired to real-world problems such as data mining.
This module will explore current methodologies in the field of signal and image processing, covering a range of aspects in capturing, processing, analysing and interpreting n-dimensional content.
The aim is to offer students with a deep understanding and to allow an exposure to the latest developments in signal and image processing, equipping them with knowledge in practical depth. The module will also provide training in programming skills (e.g. Matlab), tools and methods that are necessary for the implementation of such systems.
The module will also cover applications of signal and image processing in various fields, allowing the students the chance to establish a full awareness of technology advances in this rapidly evolving field.
This module explores current methodologies in the field of big data analytics and modelling, covering a range of aspects in collecting, transforming, processing, analysing and make inferences out of large amounts of data, which can either be signals or visual data.
The aim is to offer students a deeper understanding and to allow an exposure to the latest developments in big data analytics, equipping them with knowledge in practical depth. The module will also provide training in programming skills (e.g. python), tools and methods (e.g. Apache Spark, Spark Machine/Deep Learning, distributed analytics, etc.) that are necessary for the implementation of big data analytics systems.
The module will also cover applications of big data analytics in various fields, such as Cybersecurity, Internet of Things, and Computer Vision, allowing students the chance to establish a full awareness to the technology advance in this rapidly evolving field.
This module aims to explore current methodologies in the field of computer vision, covering a range of aspects in capturing, processing, analysing and interpreting rich visual content.
The aim is to offer students with a deep understanding and to allow an exposure to the latest developments in computer vision, equipping them with knowledge in practical depth. The module will also provide the opportunity for training in programming skills (e.g. Matlab), tools and methods that are necessary for the implementation of computer vision systems.
The module will also cover applications of computer vision in various fields, such as in object recognition/tracking, medical image analysis, multimedia indexing and retrieval and intelligent surveillance systems, allowing the students the opportunity to establish a full awareness to the technology advance in this rapidly evolving field.
This module introduces cutting-edge topics in machine learning and computer vision research areas, including both theory and practical applications. The module will follow a research seminar format, involving input from colleagues across the School of Computer Science and other Schools at Lincoln. Additionally, guest lectures from industry representatives and leading international researchers will be offered. Students will further benefit from opportunities to discuss potential research topics that they can explore to build and enhance their research and critical thinking skills.
The module introduces the fundamentals of neural computing, an emergent specialised area of computer science that is concerned to describe how the brain “computes” by simplifying neuronal biology to a set of equations.
Emphasis will be given on mathematical descriptions and computational techniques used to study and understand neurons and network of neurons. Specific topics will cover synaptic transmission and plasticity, learning and memory and vision processing including applications in object recognition and scene understanding.
Students can develop an understanding of core neural computing concepts and models, the current vision technology landscape, and topical application scenarios using a number of computational tools.
This module is designed to cover the fundamental skills and background knowledge that students need to undertake research related to the title of the award being studied, including: surveying literature; selecting and justifying a research topic; planning of research; selection of appropriate research methods; evaluation of research; presentation and reporting of research; and legal, social, ethical and professional considerations.
This module presents students with the opportunity to carry out a significant inquiry-driven research project, focusing on a topical area of interest that is aligned with their programme of study. This is primarily realised through the development of a dissertation and substantive research and/or software implementation output.
The research project is an individual piece of work, which enables students to apply and integrate elements of study from a range of modules, centred on a specific research question. The student will undertake work that is relevant to the ongoing research in either one of the established research centres within the School of Computer Science or through the development of a project concept in consultation with their allocated academic supervisor.
† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.
We want you to have all the information you need to make an informed decision on where and what you want to study. In addition to the information provided on this course page, our What You Need to Know page offers explanations on key topics including programme validation/revalidation, additional costs, and contact hours.
A brilliant and well-structured programme that encompasses all necessary modules for someone looking to enter the industry as an engineer or researcher. With state-of-the-art facilities and devoted lecturers, you will be encouraged to pursue excellence.
Diogo Ribeiro
Graduate and Data Scientist at YouLend
The programme may be assessed through a variety of means, including in-class tests, coursework, projects, and examinations. The final stage research project provides further opportunity to specialise and to complete an extended piece of work.
Our students are primarily based in the University’s Isaac Newton Building. Technical resources include computer laboratories with high-performance workstations equipped with full software development platforms. There is a range of equipment for loan, including Raspberry Pi devices, robots, and virtual reality equipment such as HTC Vive and Oculus Quest.
Students in Artificial Intelligence are taught by academics with specialist experience in areas including brain-inspired AI, medical imaging, computer vision, machine learning, neurobotics, data analytics, and parallel computing. The School of Computer Science's highly active research centres are focused on world-leading developments in computer vision, robotics and autonomous systems, and agri-food technologies, with strong links to many industrial collaborators and other universities around the world. We aim to incorporate as much of our research as possible into our taught curriculum and we provide students with opportunities to get involved in our exciting cutting-edge research activity.
Throughout the course, I gained better insights into the data analysis segment and improved my analytical thinking. I am happy I went through this programme as it helped me expand my skill set and secure a job as a Data Quality Analyst for an analytics software company.
Kosta Yankov
Below you can find examples of previous student project work. These projects may give you a feel for the areas of study you might wish to pursue during your final project on the programme.
Shashank Boite — 3D Reconstruction Of Strawberries In Complex Outdoor Environments To Assist Evaluation And Picking Tasks
Nathan Little — An Attempt to Identify Humpback Whales from Flukes Using Similarity Comparison Neural Networks
Joshua McKone — A Machine Learning Based Classification System for Brain Signals
Miguel Moreno-Rodriguez — Segmentation Of Esophageal Abnormalities In Endoscopic Images With Mask R-CN
Postgraduate Application Support
Applying for a postgraduate programme at Lincoln is easy. Find out more about the application process and what you'll need to complete on our How to Apply page. Here, you'll also be able to find out more about the entry requirements we accept and how to contact us for dedicated support during the process.
An informal interview by Skype with the Programme Leader may also be required to make sure candidates have the right background for the course. This informal contact may also include requests for samples of self-directed project work involving a significant element of software and/or systems development.
There are two requirements and you will need to provide evidence of both of them in your application:
- A first or upper second class honours degree in computer science or a related discipline. This could include engineering, mathematics, physics, or other numerate science and technology subjects.
- Competence in computer programming. Acceptable forms of evidence of this skill to include in your application include, but are not limited to: (a) academic degree transcript showing 2:1 level scores in one or more programming classes; (b) a copy of a university, employment, or hobby project report detailing programming work; (c) a link to a source code site such as gitlab or github containing samples of your code; (d) a certificate of completion of an online programming course and exam such as https://www.udemy.com/course/the-complete-python-developer-certification-course/ or https://www.udemy.com/course/learn-basics-of-c/.
If you have a good numerate degree but no programming experience then you may be able to satisfy the requirements by self-studying programming and passing a programming test online, such as through the above links. This may take a few weeks or months of part-time study depending on your previous knowledge. It is quite common for students to apply in this way.
If your application does not include sufficient evidence of both of the above, you may be asked to provide samples of self-directed project work or to have an informal conversation to clarify them.
If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages for information on equivalent qualifications.
https://www.lincoln.ac.uk/studywithus/internationalstudents/entryrequirementsandyourcountry/
Overseas students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page.
If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-sessional English and Academic Study Skills courses. These specialist courses are designed to help students meet the English language requirements for their intended programme of study.
You will need to have funding in place for your studies before you arrive at the University. Our fees vary depending on the course, mode of study, and whether you are a UK or international student. You can view the breakdown of fees for this programme below.
The University offers a range of merit-based, subject-specific, and country-focused scholarships for UK and international students. To help support students from outside of the UK, we offer a number of international scholarships which range from £1,000 up to the value of 50 per cent of tuition fees. For full details and information about eligibility, visit our scholarships and bursaries pages.
Postgraduate Funding Options
Find out more about the optional available to support your postgraduate study, from Master's Loans to scholarship opportunities. You can also find out more about how to pay your fees and access support from our helpful advisors.
This programme aims to provide students with skills spanning two key disciplines of modern computing and its applications, namely imaging and data science, and their combined use. Such skills are in high demand not only in academia and industries dealing with imaging technologies and related challenges, but also in many other areas where analytical and multidisciplinary mindsets and skills are critical. Some students may choose to continue towards doctoral level, including within the School of Computer Science.
For more information about this course, please contact the Programme Leader.
Heriberto Cuayahuitl Portilla
HCuayahuitl@lincoln.ac.uk
To get a real feel for what it is like to study at the University of Lincoln, we hold a number of dedicated postgraduate events and activities throughout the year for you to take part in.
