This programme is designed to equip you with the advanced knowledge and skills to develop the innovative solutions required by today’s rapidly advancing computing industry.
Developments in artificial intelligence, computer vision, robotics, mobile technology and games applications have all become a normal part of society’s interaction with computing devices.
This MSc Computer Science provides the opportunity to enhance your existing knowledge of computer programming and mathematical frameworks through laboratory workshops, lectures, debates and independent research.
Working alongside our staff, you will have the chance to develop your critical understanding and gain practical experience in innovative areas such as computer vision and surveillance, robotics and mobile computing in order to develop innovative solutions to current and future challenges.
In particular, students can experience a blend of different approaches. The programme aims to enable the acquisition of skills through practical workshops in the laboratory and develop 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 consists of one term of intensive study and laboratory based work with the exception of the final research project module, which is carried out over the last three months of the programme.
Each module consists typically 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/or examinations. Weekly contact hours on this programme may vary depending on the individual module options chosen and the stage of study.
The individual project is the final element of the programme. This requires students to undertake guided, independent study.
The programme is 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 in class students are expected to spend at least two - three hours in independent study.
For more detailed information please contact the programme leader.
Advanced Artificial Intelligence (Core)
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This module covers 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.
Advanced Programming (Core)
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This module will explore advanced topics using a contemporary object-oriented programming language. The objective is to prepare students for professional-level programming in scientific and commercial computing, and to support programming tasks in other modules of this award.
Students will explore a range of programming topics through a series of lectures and practical workshops, and will work on producing an individual programming assignment.
Advanced Software Engineering (Core)
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This module provides students with advanced concepts of Software Engineering principles and practices. Students will explore up-to-date methodologies and their application to real-world products and services will be covered.
Indicative topics of study will include (but are not limited to):
• Agile methods of software engineering;
• Requirements engineering, design, software components, software reuse, verification and validation, maintenance and configuration management, software evolution;
• Critical system development and the ethical implications of software engineering;
• Fault Tree Analysis.
Computer Vision (Core)
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This module will 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 develop a deeper understanding and to allow an exposure to the latest developments in computer vision, equipping students 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 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 students the chance to establish a full awareness of the technology advances in this rapidly evolving field.
Machine Learning (Core)
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This module covers 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.
Mobile and Connected Devices (Core)
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This module explores the cutting-edge computing concepts and in-the-field deployment of emerging Internet of Things (IoT) platforms and devices. The module will investigate, through practical implementation, the low-barrier capture, communication, and highly scalable consumption of data from geographically dispersed physical objects and sensors, with a view to creating novel end-user experiences. Physical objects can now be easily connected to the internet and other objects through small, low-power, and inexpensive lightweight computing devices; creating hugely scalable networks of ‘things’ that can interoperate and stream data using simple web standards such as REST. IoT enabled objects and infrastructure can enable unforeseen opportunities for novel application scenarios, data collection and consumption, as well as create new markets around open data and third party applications. Additionally, the module will cover how emerging capability such as locative and context aware technology can be exploited in cloud-connected prototypes and mobile applications. In terms of practical development, special attention is given to: creating data stream assets from sensor boards and smartphones, building a cloud information hub to store sensor data, and developing cloud services for consumption by mobile and other third party applications. Students will be asked to design and prototype IoT enabled applications, based on themed societal issues, using a combination of development boards and sensors, cloud computing services, and mobile applications.
Research Methods (MSc Computer Science) (Core)
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This module covers the fundamental skills and background knowledge that students need to undertake research, including: surveying literature; selecting and justifying a research topic; selection of appropriate research methods, including consideration of quantitative versus qualitative methods; analysis of research data; evaluation of research; presentation and reporting of research; and legal, social, ethical and professional considerations.
Research Project (Core)
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This module gives students with the opportunity to carry out a significant project, focusing on an area of particular personal and professional interest, through the development of a dissertation and substantive software implementation.
The research project is an individual piece of work, which gives students the chance to apply and integrate elements of study from a range of modules, centred on a specific research question. Students are expected to undertake work that is relevant to the ongoing research in one of the established research centres within the Lincoln School of Computer Science and will work closely under the supervision of a member of that research centre.
Students are required to undertake the development of a software artefact that is non-trivial in scale and goals, and is supported by best-practice application of appropriate theoretical frameworks.
The final stage research project provides the opportunity to specialise and to complete a piece of work of significant complexity.
The University of Lincoln's policy on assessment feedback aims to ensure that academics will return in-course assessments to you promptly – usually within 15 working days after the submission date.
Much of the School of Computer Science's research is internationally recognised and areas of expertise currently include computer vision and medical imaging, autonomous systems and robotics, and human-computer interaction.
(including Alumni Scholarship 25% reduction)**
(Including International Alumni / Global Postgraduate Scholarship £2,000 reduction)**
|Part-time Home/EU||£41 per credit point|
|Part-time International||£87 per credit point|
* Academic year September- July
** Subject to eligibility
As a postgraduate student you may be eligible for scholarships in addition to those shown above.
To complete a standard Master's Taught programme, you must complete 180 credit points.
Full time students will be invoiced for the programme in full upon initial enrolment.
For part-time students, tuition fees are payable each credit point enrolled. To calculate your part-time fees, multiply the part-time fee per credit point by the number of credits you intend to complete within that academic year. This is usually between 60 and 90 credit points per year.
For example, if the fee per credit point for your programme is £38, and you enrol on 60 credits, the tuition fee payable for that academic year will be £2280.
Tuition fees for additional activity are payable by the student/sponsor and charged at the equivalent £ per credit point rate for each module. Additional activity includes:
- Enrolment on modules that are in addition to the validated programme curriculum
- Enrolment on modules that are over and above the full credit diet for the relevant academic year
- Retakes of modules as permitted by the Board of Examiners
Exceptionally tuition fees may not be payable where a student has been granted a retake with approved extenuating circumstances.
For further information and for details about funding your study, scholarships and bursaries, please see our Postgraduate Fees & Funding pages [www.lincoln.ac.uk/home/studyatlincoln/postgraduateprogrammes/feesandfunding/].
With regards to text books, the University provides students who enrol with a comprehensive reading list and you will find that our extensive library holds either material or virtual versions of the core texts that you are required to read. However, you may prefer to purchase some of these for yourself and you will be responsible for this cost.
Throughout this degree, students may receive tuition from professors, senior lecturers, lecturers, researchers, practitioners, visiting experts or technicians, and they may also be supported in their learning by other students.
Dr Bashir Al-Diri
Dr. Bashir Al-Diri is a Senior Lecturer at the University of Lincoln, and member of the Laboratory of Vision Engineering in the School of Computer Science. He developed a robust fully automated system for retinal vascular segmentation and measurement, and his areas of research include: deep learning, computer vision, medical image analysis, automated surveillance, artificial intelligence, speech recognition and language corpus and lexical analysis.
This programme aims to develop the knowledge and specialist skills necessary to progress to roles in the computing and technology industries. Some may choose to continue to research at doctoral level.
The University Careers and Employability Team offer qualified advisors who can work with you to provide tailored, individual support and careers advice during your time at the University. As a member of our alumni we also offer one-to-one support in the first year after completing your course, including access to events, vacancy information and website resources; with access to online vacancies and virtual and website resources for the following two years.
This service can include one-to-one coaching, CV advice and interview preparation to help you maximise your future opportunities.
The service works closely with local, national and international employers, acting as a gateway to the business world.
Visit our Careers Service pages here http://bit.ly/1lAS1Iz.
At Lincoln, we constantly invest in our campus as we aim to provide the best learning environment for our students. Whatever the area of study, the University strives to ensure students have access to specialist equipment and resources, to develop the skills, which they may need in their future career.
Technical resources for Computer Science include research facilities and laboratories, a computer engineering workshop, workstations with full development software platforms and a range of equipment for loan including, Raspberry Pi, Oculus Rift and HTC Vive virtual reality kit, smartphones and robots.
Students can study and research in the University's Great Central Warehouse Library, which provides more than 250,000 printed books and approximately 400,000 electronic books and journals, as well as databases and specialist collections. The Library has a range of different spaces for shared and individual learning.