Course Information
Select year of entry:
4-5 years 8 years School of Computer Science Lincoln Campus [L] Validated BBB (or equivalent qualifications) G404 4-5 years 8 years School of Computer Science Lincoln Campus [L] Validated BBB (120 UCAS Tariff points) (or equivalent qualifications) G404

Introduction

The MComp Computer Science degree is a four-year, integrated Master's degree is designed to give the experience, skills and knowledge to design and develop a variety of software and hardware computing solutions for real-world problems.

The MComp degree pays particular attention to cutting-edge topics, such as artificial intelligence and human-computer interaction, in addition to core computer science disciplines. This aims to ensure that your studies are at the forefront of research in the field. In addition, you are encouraged to work with academics on research projects, such as with Marc the robot.

Marc the robot was created by Dr John Murray at our School of Computer Science. He is helping scientists understand how long-term relationships might be developed between humans and androids. Third-year students are looking at ways to make MARC hear and respond to sounds and are developing remote control systems for his hands and arms. First-year students are working on vision-based programmes to teach him to play rock, paper, scissors.

This degree aims to provide a broad foundation in computer science and students can develop the mathematical, analytical and problem-solving skills required to succeed in the challenging and exciting modern computing industry. With digital technologies driving advances in all aspects of the modern world, from business to healthcare to education, those with expertise in computer science are finding employment in a wide range of sectors.

Accreditations

This course is accredited by The British Computer Society

The University of Lincoln is also affiliated with The Institution of Analysts and Programmers.

How You Study

Full-time or part-time study is available.

In your first year, you have the opportunity to study the fundamental areas of computing science. This includes programming, computer architectures, operating systems and maths for computing.

The second year aims to build on this foundation, covering artificial intelligence and database and network systems. At this stage, you will have the chance to specialise in topics such as image processing, robotics and parallel computing. You will also have the opportunity to work on an extended group project.

In the third year, you can choose an optional area of study that is of specific interest to you, such as mobile computing or business intelligence, while completing a substantial individual project.

In the fourth year you have the chance to broaden your knowledge further by taking optional modules and by undertaking a Master's level project.

Contact Hours and Independent Study

Contact hours may vary for each year of a degree. When engaging in a full-time degree students should, at the very least, expect to undertake a minimum of 37 hours of study each week during term time (including independent study) in addition to potentially undertaking assignments outside of term time. The composition and delivery for the course breaks down differently for each module and may include lectures, seminars, workshops, independent study, practicals, work placements, research and one-to-one learning.

University-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 two - three hours in independent study.

On each of our course pages you can find information on typical contact hours, modes of delivery and a breakdown of assessment methods. Where available, you will also be able to access a link to Unistats.com, where the latest data on student satisfaction and employability outcomes can be found.

How You Are Assessed

The course is assessed through a variety of means, including in-class tests, coursework and examinations, the majority of assessments are coursework- based.

Assessment Feedback

The University of Lincoln's policy on assessment feedback aims to ensure that academics will return in-course assessments to students promptly – usually within 15 working days after the submission date (unless stated differently above)..

Methods of Assessment

The way students will be assessed on this course will vary for each module. It could include coursework, such as a dissertation or essay, written and practical exams, portfolio development, group work or presentations to name some examples.

For a breakdown of assessment methods used on this course and student satisfaction, please visit the Unistats website, using the link at the bottom of this page.

Throughout this degree, students may receive tuition from professors, senior lecturers, lecturers, researchers, practitioners, visiting experts or technicians, and they may be supported in their learning by other students.

Staff

Throughout this degree, students may receive tuition from professors, senior lecturers, lecturers, researchers, practitioners, visiting experts or technicians, and they may be supported in their learning by other students.

For a comprehensive list of teaching staff, please see our School of Computer Science Staff Pages.

Entry Requirements 2017-18

GCE Advanced Levels: BBB

International Baccalaureate: 30 points overall

BTEC Extended Diploma: Distinction, Distinction, Merit

Access to Higher Education Diploma: A minimum of 45 level 3 credits at merit or above will be required.

We will also consider extensive, relevant work experience; please email admissions@lincoln.ac.uk with full details for further advice.

In addition, applicants must have at least 3 GCSEs at grade C or above in English and Maths. Level 2 equivalent qualifications such as BTEC First Certificates and Level 2 Functional Skills will be considered


International Students will require English Language at IELTS 6.0 with no less than 5.5 in each element, or equivalent. http://www.lincoln.ac.uk/englishrequirements

If you would like further information about entry requirements, or would like to discuss whether the qualifications you are currently studying are acceptable, please contact the Admissions team on 01522 886097, or email admissions@lincoln.ac.uk.

Level 1

Algorithms and Complexity (Core)

The module aims to introduce the concepts of Algorithms and Complexity, providing an understanding of the range of applications where algorithmic solutions are required.

Students will have the opportunity to be introduced to the analysis of time and space efficiency of algorithms; to the key issues in algorithm design; to the range of techniques used in the design of various types of algorithms. Students can also be introduced to relevant theoretical concepts around algorithms and complexity in the lectures, together with a practical experience of implementing a range of algorithms in the workshops.

Computer Architectures (Core)

This module aims to introduce the fundamentals of computer hardware underpinning the key aspects of Computer Science. This knowledge is not only essential for deeper understanding of the governing processes behind computing but also for realising how hardware interacts with software.

By studying Computer Architecture, students can gain greater confidence in their study subject and future benefits when improving their programming skills. The module will study the individual components of a computer system, their function, main characteristics, performance and their mutual interaction. Examples of the practical application of the skills developed in this module are given utilising a range of computing applications, including but not restricted to the domains of Games and Social Computing applications.

Maths for Computing (Core)

This module aims to equip students with mathematical knowledge and skills required to design and develop computer systems and software.

Operating Systems (Core)

In this module students will have the opportunity to study both the theoretical design concepts which underpin all operating systems and, through case studies, the practical implementation techniques of current operating systems. Special attention will be given to shell programming languages and examples, to practically implement concepts and techniques at the basis of the various operating systems.

Problem Solving (Core)

Problems are a natural occurrence in an organisational context and this module aims to introduce students to problem solving from a mixture of theoretical and practical underpinnings.

The module examines the principles of abstraction, decomposition, modelling and representation as a means to frame and characterise problem scenarios, and as tools to understand potential solutions. The module concentrates on problem-solving strategies and in particular the vocabulary through which these strategies are articulated. This type of vocabulary is explored as representational device for capturing organisational behaviour and form.

Programming and Data Structures (Core)

This module aims to introduce the concepts and practice of simple computer programming, with attention paid to the fundamentals that constitute a complete computer program including layout, structure and functionality.

The module aims to extend students' knowledge of computer programming and introduces them to fundamental computing data structures allowing the representation of data in computer programs.

Web Authoring (Core)

This module aims to provide students with the knowledge to design and implement interactive client-side web technologies. Students have the opportunity to learn key concepts in web markup languages; notably the features and capabilities that are part of the HTML5 specification standard including multimedia elements, the canvas element, and local web storage.

Additionally students will have the opportunity to develop technologies that are part of the wider HTML5 family such as CSS3, geolocation, drag and drop, and javascript. A standards driven approach will be adopted throughout the module using web page validation techniques, with emphasis on the importance of separating web page style and structure.

Level 2

Artificial Intelligence (Core)

This module aims to provide a basic introduction to the field of Artificial Intelligence (AI).

The module first considers the symbolic model of intelligence, exploring some of the main conceptual issues, theoretical approaches and practical techniques. The module further explores knowledge-based systems such as expert systems, which mimic human reasoning performance by capturing knowledge of a domain and integrating it to deliver a performance comparable to that of a human practitioner. Modern developments such as artificial neural networks and uncertain reasoning are also covered using probability theory, culminating in a practical understanding of how to apply AI techniques in practice using logic programming.

Database Systems (Core)

In this module students will have the opportunity to explore the fundamental concepts necessary for designing, implementing and using database systems, which require the students to develop a conceptual view of database theory and then transform it into a practical design of a database application.

Alternate design principles for implementing databases for different uses, for example in Social Media or Gaming contexts are also considered.

Group Project (Core)

This module aims to provide students with the experience of working as part of a team on a development project. Students will have the opportunity to produce a set of deliverables relevant to their programme of study, including a finished product or artefact. Final deliverables will be negotiated between the group and their supervisor, the module coordinator will be responsible for ensuring that each project covers the learning outcomes of the module.

Groups are expected to manage their own processes, and to hold regular meetings both with and without their supervisor. Groups will be allocated by the module coordinator and other members of staff. The process of development of the artefact and the interaction and management of group members underpins the assessment of skills in the module.

Human-Computer Interaction (Core)

In this module students will have the opportunity to form an appreciation of the importance of human factors and user-centred approaches in the development of technological systems (analysis, design, implementation and evaluation of technological systems).

Students will be introduced to the physiological, psychological and cognitive issues relevant to human computer interaction and user-interface design.

Networks and Network Systems (Core)

In this module students may consider basic computer communications and networking with an emphasis on the Internet protocol. Internet protocol will be examined as a model for intercommunication in modern network implementations. Additionally students will have the opportunity to explore fundamental design features of a Network Protocol and the need to implement security in the modern Internet.

Object-Oriented Programming (Core)

This module aims to provide a comprehensive analysis of the general principles and practices of advanced programming with respect to software development. Notions and techniques of advanced programming are emphasised in the context of analysis, design and implementation of software and algorithms.

Great importance is placed upon the Object-Oriented paradigm and related concepts applied to algorithm and software development.

Professional Practice (Core)

Professional Practice aims to develop an understanding of the basic cultural, social, legal, and ethical issues inherent in the discipline of computing; and to promote personal professionalism in the workplace. Examples of topics covered include:

  • The special nature of technological ethics.
  • Ethical decision-making and case analysis.
  • Ethics of software development.
  • Legal issues in the field of technology.
  • Codes of computer ethics and professional practice.
  • Globalisation of professionalism.
  • Professional engagement with the job applications process.

Programming Paradigms (Core)

This module provides students with a theoretical overview of the different programming paradigms, specifically Procedural, Object-Oriented, Functional and Logical paradigms.

Comparative techniques are used to explain the differences between them and practical application of example problem scenarios are used to provide the means to contextualise the advantages and disadvantages of each.

Other modules in the programme concentrate the student on procedural and object-oriented programming approaches as their core framework, and the AI module delivers the key aspects of the logical paradigm. This module therefore presents the students with the underpinning theories and principles of functional programming, through mathematical definitions of programme requirements and the application of recursion to create problem solving solution mechanisms.

Level 3

Algorithms for Data Mining (Option)

The module examines the mathematical fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will learn the fundamentals of data science, including basic terminology and concepts, core models, current technology landscape, and topical application scenarios using cloud platforms and open datasets. Students will be introduced to a basic data scientist toolkit that can be applied to design/build data-driven applications, and provide insights into diverse datasets.

Autonomous Mobile Robotics (Core)

The module aims to introduce the main concepts of Autonomous Mobile Robotics, providing an understanding of the range of processing components required to build physically embodied robotic systems, from basic control architectures to spatial navigation in real-world environments.

Students will have the opportunity to be introduced to relevant theoretical concepts around robotic sensing and control in the lectures, together with a practical “hands on” approach to robot programming in the workshops.

Business Intelligence (Option)

Business Intelligence (BI) refers to technologies, applications, and practices for the collection, integration, analysis, and presentation of meaningful and useful information for business purposes.

The purpose of the module is to understand the issues involved in the use and application of these ‘tools’ and how BI might be applied to generate creative and novel insight helping support better business decisions. BI systems are data-driven Decision Support Systems. They provide historical, current, predictive and insightful views of business operations, most often using data gathered from data warehouses. Software elements support reporting, interactive 'slice-and-dice' pivot-table analyses, visualization, and statistical data mining.

Critical Perspectives on Project Management (Option)

The module 'Critical Perspectives on Project Management' aims to explore the practical issues and challenges of putting technology to work.

As technology grows and becomes ever more pervasive, the size, complexity and timescales of related projects grow too. The challenges facing project managers involved in planning, coordinating, directing and implementing technology based projects on-time, to budget and operationally as expected is ever growing. This module aims to develop a critical perspective of project management and uses case based material to develop an understanding about the various challenges project management in this arena presents. Students are encouraged to reflect on the limits of certain forms of rational project management modes in conditions that are more accurately described in terms of uncertainty, complexity, risk and chaos.

Cross-Platform Development (Option)

This module aims to provides students with knowledge on an alternative, and increasingly important, ‘platform agnostic’ approach for mobile development. This approach embraces the use of cross-platform methods by developing applications with a single code base that run efficiently across distinct mobile platforms, with maximum code reuse and interoperability.

Students will have the opportunity to investigate platform-dependent constraints by critiquing the emergent space of cross-platform tools and frameworks that aim to maximise code sharing between mobile platforms, whilst retaining common like-for-like sensor features such as geolocation, camera, storage and push notification’s without compromising performance or overall user experience. Contemporary cross-platform tools will be adopted throughout the module for the creation of applications that bridge multiple mobile platforms.

Cyber Security in Society (Option)

This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social and ethical implications of cyber security.

Data Science Tools and Techniques (Option)

The module introduces the fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will consider the societal, ethical and professional requirements for and uses of data science and be exposed to core concepts and models, the current technology landscape, and topical application scenarios using cloud platforms and open datasets.

Entrepreneurship and Innovation 1 (Option)

This module aims to provide the business context for activities supported by and delivered through computing technologies.

Students may investigate the drivers for modern Electronic Business and consider enterprise applications from a business viewpoint. Students can explore the process of taking a technologically grounded idea, and develop a business case through break-even point to where profitability begins and specify an appropriate web site as the vehicle to deliver the business case. The Entrepreneurial perspective considers business development as a holistic process, students can engage with this notion throughout the module. The module will also draw upon examples and themes from social computing, the importance of which is growing rapidly in importance.

Entrepreneurship and Innovation 2 (Option)

This module aims to build on the principles of 'Entrepreneurship & Innovation 1' and applies formalised methods and approaches in the exploration of specific areas of entrepreneurship and innovation. The module will also investigate the application of social computing principles, game theory and cooperation analysis in the development of an entrepreneurial idea.

Image Processing (Core)

Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection, medical imaging, etc. It is the study of any algorithms that take image as an input and returns useful information as output.

This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from the raw image and interpret the image data — the techniques will be implemented using the mathematical programming language Matlab or OpenCV.

Mobile Computing (Option)

This module provides students with the opportunity to develop knowledge in the specification and development of connected ‘data-driven’ mobile applications, using industry standard tools and guidelines.

Mobile device platforms, such as smartphones can provide a rich development experience with direct access to a number of pervasive sensors such as GPS, camera, proximity, NFC and multiple network connectivity channels. These sensors are used as building blocks for lifestyle-supporting mobile applications in areas such as health, fitness, social, science, and entertainment. Such applications are now seen as part of the everyday fabric of life. Students can learn how to develop topically-themed native mobile applications that consume RESTful web services. Data privacy and security issues are discussed throughout the module.

Parallel Computing (Core)

Parallel Computing is a very important, modern paradigm in Computer Science, which is a promising direction for keeping up with the expected exponential growth in the discipline.

Executing multiple processes at the same time can tremendously increase the computational throughput, not only benefitting scientific computations but also leading to new exciting applications like real-time animated 3D graphics, video processing, physics simulation, etc. The relevance of parallel computing is especially prominent due to availability of modern, affordable computer hardware utilising multi-core and/or large number of massively parallel units.

Project (Computer Science) (Core)

This module provides students with an opportunity to demonstrate their ability to work independently on an in-depth project with an implementation element that builds on their established knowledge, understanding and skills.

Students will normally be expected to demonstrate their ability to apply practical and analytical skills, innovation and/or creativity, and to be able to synthesise information, ideas and practices to provide a problem solution. Self-management is a key concept here, as is the ability to engage in critical self-evaluation.

Software Engineering (Core)

The module covers advanced topics of Software Engineering, focusing on software methodologies, with respect to changes in the software development process including past and present techniques.

Key Software Engineering principles are explored in the context of real world software engineering challenges such as software evolution and reuse. Topics such as advanced testing, verification and validation, critical systems development, re-factoring and design patterns will be covered.

Masters Level

Advanced Artificial Intelligence (Option)

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.

Advanced Programming (Option)

This module aims to 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 can 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 (Option)

This module aims to provide students with advanced concepts of Software Engineering principles and practices. Students can 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 (Option)

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.

Machine Learning (Option)

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.

Mobile and Connected Devices (Option)

This module aims to explore 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 aim to 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 given the opportunity 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)

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.

Level 4

Algorithms for Data Mining (M) (Option)

The module examines the mathematical fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will learn the fundamentals of data science, including basic terminology and concepts, core models, current technology landscape, and topical application scenarios using cloud platforms and open datasets. Students will be introduced to a basic data scientist toolkit that can be applied to design/build data-driven applications, and provide insights into diverse datasets.

Business Intelligence (M) (Option)

Business Intelligence (BI) refers to technologies, applications, and practices for the collection, integration, analysis, and presentation of meaningful and useful information for business purposes. The purpose of the module is to understand the issues involved in the use and application of these ‘tools’ and how BI might be applied to generate creative and novel insight helping support better business decisions. BI systems are data-driven Decision Support Systems. They provide historical, current, predictive and insightful views of business operations, most often using data gathered from data warehouses. Software elements support reporting, interactive 'slice-and-dice' pivot-table analyses, visualization, and statistical data mining.

Working at Masters level, students will have the opportunity to research the area in-depth and produce critical reports of their findings.

Critical Perspectives on Project Management (M) (Option)

The module 'Critical Perspectives on Project Management' aims to explore the practical issues and challenges of putting technology to work. As technology grows and becomes ever more pervasive, the size, complexity and timescales of related projects grow too. The challenges facing project managers involved in planning, coordinating, directing and implementing technology based projects on-time, to budget and operationally as expected is ever growing. This module aims to develop a critical perspective of project management and uses case-based material to develop an understanding about the various challenges project management in this arena presents. Students are encouraged to reflect on the limits of certain forms of rational project management modes in conditions that are more accurately described in terms of uncertainty, complexity, risk and chaos.

Working at Masters level, students can research the area in-depth and produce critical reports of their findings.

Cyber Security in Society (M) (Option)

This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social and ethical implications of cyber security. As a Masters level module students are also encouraged to consider current research in the field of cyber security.

Data Analytics and Visualisation (Option)

This module aims to develop students' understanding of contemporary approaches to data analysis and visualisation. The module places particular emphasis on making sense of large datasets such as those generated from social media interactions or other web sources. It delivers material on the fundamental understanding of human visual perception and the political and persuasive power of data, and develops this alongside the use of standard tools for data collection, processing, manipulation, analysis and visual presentation. The practical role of data analytics and visualisation in media and business contexts is a core thread running through the module.

Data Science Tools and Techniques (M) (Option)

The module introduces the fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will consider the societal, ethical and professional requirements for and uses of data science and be exposed to core concepts and models, the current technology landscape, and topical application scenarios using cloud platforms and open datasets.

Entrepreneurship and Innovation 1 (M) (Option)

In this module students have the opportunity to investigate the drivers for modern Electronic Business and consider enterprise applications from a business viewpoint. Students can explore the process of taking a technologically grounded idea and develop a business case to the point where profitability begins.

Working at Masters level, students can research the area in-depth and produce critical reports of their findings.

MComp Research Project (Core)

The MComp Research Project is an individual piece of work that expects students to apply and integrate theoretical knowledge and practical skills from the breadth of their experience with computer science sub-disciplines, in order to address a specific research question or questions formulated with support from academic staff.

The form and nature of this project is negotiable, but at MComp Level 4 there are typically three types of Project that are undertaken:

  • Industrial Based Project work (typically engaged with through a work placement)
  • Client-based project delivery (typically with an approved client in either public, private or third sector partners, and with a clearly articulated delivery)
  • A research based project (typically done in conjunction with a member of academic staff in the School and with a clear linkage to research activity of the staff member but which could include collaborative projects with research groups at other Universities)

The student can undertake work that is predominantly relevant to the ongoing research in one of the established research centres within the School of Computer Science. In all cases the Project supervisor will ensure that the study undertaken is suitably grounded within the programme title of each student.

Movement Interfaces (Option)

Recent years have seen growing interest in games interfaces that require movement of the body, and build on the user’s physical skills and abilities; the new dimension introduces a unique set of challenges in the design of games that extends beyond traditional human-computer interaction.

This module aims to provide students with advanced understanding of theoretical and practical concerns related to the design of technology that recognizes, captures and visualizes player movement. A number of inter-disciplinary perspectives on designing for player movement are considered, such as accessibility of games for players with mobility impairments, sports, performance, dance and audience. In addition, students can engage with practical issues related to the design, development and evaluation of movement-based games.

†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.

Special Features

You are taught by academics with specialist experience in areas including computer vision and medical imaging, autonomous systems and robotics, and human-computer interaction. Much of the School's research is internationally recognised, such as a research project into medical imaging by Distinguished Professor of Image Engineering, Nigel Allinson MBE, who was recently awarded a £1.6 million grant from the Wellcome Trust.

Study Visits

Overseas study visits have been a feature of our courses in recent years. Visits aim to provide students with a unique insight into games development issues in overseas territories. Last year students had the opportunity to attend a summer school in China with our partner, Sichuan University, and work alongside students from a number of countries to develop skills in Mobile App Development as well as having free time to visit the local panda breeding centre (the total cost for each student was approximately £300, based on 2015 costs).

Placements

This degree is optionally available in a sandwich mode variant. If students choose the sandwich placement option, they take a year out in industry between years Two and Three, gaining invaluable industrial experience. Students are supported throughout their placement, which can be overseas. There are opportunities to take shorter work placements and to be involved in systems development projects for real clients.

Sandwich students, in general, tend to do well at the final level, and may find they have enhanced job prospects. Students must apply specifically for the sandwich variant; if they join via the standard route we may not allow a transfer to the sandwich variant, as places are limited.

Placement Year

When students are on an optional placement in the UK or overseas or studying abroad, they will be required to cover their own transport and accommodation and meals costs. Placements can range from a few weeks to a full year if students choose to undertake an optional sandwich year in industry.

Students are encouraged to obtain placements in industry independently. Tutors may provide support and advice to students who require it during this process.

Student as Producer

Student as Producer is a model of teaching and learning that encourages academics and undergraduate students to collaborate on research activities. It is a programme committed to learning through doing.

The Student as Producer initiative was commended by the QAA in our 2012 review and is one of the teaching and learning features that makes the Lincoln experience unique.

Facilities

Technical resources for Computer Science include research facilities and laboratories, a computer engineering workshop, workstations with full design software platforms and a range of equipment for loan including Raspberry Pi, Oculus Rift virtual reality kit, tablets, smartphones and robots.

At Lincoln, we constantly invest in our campus as we aim to provide the best learning environment for our undergraduates. 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.

View our campus pages [www.lincoln.ac.uk/home/campuslife/ourcampus/] to learn more about our teaching and learning facilities.

Career Opportunities

This degree aims to equip graduates with the mathematical, analytical and problem-solving skills that make them well placed for computer and IT-related roles across a range of sectors. Lincoln graduates have gone on to work for 3t Logistics, the NHS, Open GI, Boots and Anglian Water. Some graduates go on to study for a PhD-level qualification.

Careers Service

The University Careers and Employability Team offer qualified advisors who can work with students to provide tailored, individual support and careers advice during their time at the University. As a member of our alumni we also offer one-to-one support in the first year after completing a course, including access to events, vacancy information and website resources; with access to online vacancies and virtual resources for the following two years.

This service can include one-to-one coaching, CV advice and interview preparation to help you maximise our graduates 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 for further information. [http://www.lincoln.ac.uk/home/campuslife/studentsupport/careersservice/]

Additional Costs

For each course students may find that there are additional costs. These may be with regard to the specific clothing, materials or equipment required, depending on their subject area. Some courses provide opportunities for students to undertake field work or field trips. Where these are compulsory, the cost for the travel, accommodation and meals may be covered by the University and so is included in the fee. Where these are optional students will normally (unless stated otherwise) be required to pay their own transportation, accommodation and meal costs.

With regards to text books, the University provides students who enrol with a comprehensive reading list and our extensive library holds either material or virtual versions of the core texts that students are required to read. However, students may prefer to purchase some of these for themselves and will therefore be responsible for this cost. Where there may be exceptions to this general rule, information will be displayed in a section titled Other Costs below.

Related Courses

The MComp Computer Science degree is a four-year, integrated Master's degree is designed to give the experience, skills and knowledge to design and develop a variety of software and hardware computing solutions for real-world problems.
Electrical engineering is essential to the modern world, encompassing everything from energy and automation through to communications and transport. The BEng (Hons) Electrical Engineering programme is designed to equip students with the skills to succeed as the engineers of the future.
The BSc (Hons) Games Computing degree at Lincoln aims to develop the skills and attributes required for roles in the games and entertainment industries, including mobile, social media and console game development. Students can also learn skills relevant to work in broader technological environments.
The MComp is a four-year degree programme which enhances and extends the equivalent BSc (Hons) programme. It provides the opportunity to study a range of modules at Master’s level and to complete a substantive project in an area of specific personal interest. Studying at Master’s level enables you to both deepen and broaden your knowledge and understanding. This can provide you with a stronger CV and may give you a distinct edge in the job market.
This research-informed BSc (Hons) Mathematics degree aims to provide a fundamental education in the fascinating field of mathematics, including pure and applied mathematics. Students have opportunities to work alongside academic staff on challenging projects, which could contribute to academic research or collaboration with industry.
The research-informed MMath Mathematics degree aims to provide a fundamental education in mathematics, including pure and applied mathematics. There will be opportunities for students to develop high-level mathematical and problem-solving skills and to apply these in a variety of contexts. Students will also have the chance to work alongside fellow undergraduates and academic staff on projects.

Introduction

The MComp Computer Science degree is a four-year, integrated Master's degree is designed to give the experience, skills and knowledge to design and develop a variety of software and hardware computing solutions for real-world problems.

The MComp degree provides you with the opportunity to develop the experience, skills and knowledge to design and develop a variety of software and hardware computing solutions for real-world problems. Particular attention is paid to cutting-edge topics, such as artificial intelligence and human-computer interaction, in addition to core computer science disciplines. This aims to ensure that your studies are at the forefront of research in the field. In addition, you are encouraged to work with academics on research projects, such as with MARC the robot.

MARC the robot was built at the University by Dr John Murray in our School of Computer Science. He is helping scientists understand how long-term relationships might be developed between humans and robots. Third-year students are looking at ways to make MARC hear and respond to sounds and are developing remote control systems for his hands and arms. First-year students are working on vision-based programmes to teach him to play rock, paper, scissors.

This degree aims to provide a broad foundation in computer science and students can develop the mathematical, analytical and problem-solving skills required to succeed in the challenging and exciting modern computing industry. With digital technologies driving advances in all aspects of the modern world, from business to healthcare to education, those with expertise in computer science are finding employment in a wide range of sectors.

Accreditations

This course is accredited by The British Computer Society

The University of Lincoln is also affiliated with The Institution of Analysts and Programmers.

How You Study

Full-time or part-time study is available.

In your first year, you have the opportunity to study the fundamental areas of computing science. This includes programming, computer architectures, operating systems and maths for computing.

The second year aims to build on this foundation, covering artificial intelligence and database and network systems. At this stage, you will have the chance to specialise in topics such as image processing, robotics and parallel computing. You will also have the opportunity to work on an extended group project.

In the third year, you can choose an optional area of study that is of specific interest to you, such as mobile computing or business intelligence, while completing a substantial individual project.

Students who choose this four-year MComp programme have the opportunity to study a range of optional modules at Master’s level and to complete a project with real-world applications in an area of individual interest.

Contact Hours

Level 1:

At level one students will typically have around 14 hours of contact time per week. A typical week may consist of:

  • 6 hours of practical classes and workshops
  • 2 hours of tutorial time
  • 6 hours in lectures


Level 2:

At level two students will typically have around 14 hours of contact time per week. A typical week may consist of:

  • 6 hours of practical classes and workshops
  • 1 hour of project supervision
  • 7 hours in lectures


Level 3:

At level three students will typically have around 13 hours of contact time per week. A typical week may consist of:

  • 6 hours of practical classes and workshops
  • 1 hour of project supervision
  • 1 hour of tutorial time
  • 5 hours in lectures


Master's level:

At Master's level students will typically have around 8 hours of contact time per week. A typical week may consist of:

  • 3 hours of practical classes and workshops
  • 1 hour of project supervision
  • 4 hours in lectures


Overall Workload and Independent Study

University-level study involves a significant proportion of independent study, exploring the material covered in lectures and seminars. Students’ overall workload will consist of their scheduled contact hours combined with independent study. The expected level of independent study is detailed below.

Level 1:

  • Total scheduled teaching and learning hours: 339
  • Percentage scheduled teaching and learning hours: 28%
  • Percentage of independent study expected: 72%


Level 2:

  • Total scheduled teaching and learning hours: 338
  • Percentage scheduled teaching and learning hours: 28%
  • Percentage of independent study expected: 72%


Level 3:

  • Total scheduled teaching and learning hours: 270
  • Percentage scheduled teaching and learning hours: 23%
  • Percentage of independent study expected: 77%


Master's level:

  • Total scheduled teaching and learning hours: 192
  • Percentage scheduled teaching and learning hours: 16%
  • Percentage of independent study expected: 84%

Contact Hours and Independent Study

Contact hours may vary for each year of a degree. When engaging in a full-time degree students should, at the very least, expect to undertake a minimum of 37 hours of study each week during term time (including independent study) in addition to potentially undertaking assignments outside of term time. The composition and delivery for the course breaks down differently for each module and may include lectures, seminars, workshops, independent study, practicals, work placements, research and one-to-one learning.

University-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 two - three hours in independent study.

On each of our course pages you can find information on typical contact hours, modes of delivery and a breakdown of assessment methods. Where available, you will also be able to access a link to Unistats.com, where the latest data on student satisfaction and employability outcomes can be found.

How You Are Assessed

The course is assessed through a variety of means, including in-class tests, coursework and examinations, the majority of assessments are coursework- based.

The way students will be assessed on this course will vary for each module. It could include coursework, such as a dissertation or essay, written and practical exams, portfolio development, group work or presentations to name some examples.

Assessment Breakdown

Level 1:

Coursework: 60%
Practical exams: 0%
Written exams: 40%

Level 2:

Coursework: 65%
Practical exams: 0%
Written exams: 35%

Level 3:

Coursework: 74.3%
Practical exams: 2.1%
Written exams: 23.6%

Master's level:

Coursework: 88%
Practical exams: 3%
Written exams: 9%

Assessment Feedback

The University of Lincoln's policy on assessment feedback aims to ensure that academics will return in-course assessments to students promptly – usually within 15 working days after the submission date (unless stated differently above)..

Methods of Assessment

The way students will be assessed on this course will vary for each module. It could include coursework, such as a dissertation or essay, written and practical exams, portfolio development, group work or presentations to name some examples.

For a breakdown of assessment methods used on this course and student satisfaction, please visit the Unistats website, using the link at the bottom of this page.

Throughout this degree, students may receive tuition from professors, senior lecturers, lecturers, researchers, practitioners, visiting experts or technicians, and they may be supported in their learning by other students.

Staff

Throughout this degree, students may receive tuition from professors, senior lecturers, lecturers, researchers, practitioners, visiting experts or technicians, and they may be supported in their learning by other students.

For a comprehensive list of teaching staff, please see our School of Computer Science Staff Pages.

Entry Requirements 2018-19

GCE Advanced Levels: BBB

International Baccalaureate: 30 points overall

BTEC Extended Diploma: Distinction, Distinction, Merit

Access to Higher Education Diploma: A minimum of 45 level 3 credits at merit or above will be required.

We will also consider extensive, relevant work experience; please email admissions@lincoln.ac.uk with full details for further advice.

In addition, applicants must have at least 3 GCSEs at grade C or above in English and Maths. Level 2 equivalent qualifications such as BTEC First Certificates and Level 2 Functional Skills will be considered


International Students will require English Language at IELTS 6.0 with no less than 5.5 in each element, or equivalent. http://www.lincoln.ac.uk/englishrequirements

If you would like further information about entry requirements, or would like to discuss whether the qualifications you are currently studying are acceptable, please contact the Admissions team on 01522 886097, or email admissions@lincoln.ac.uk.

Level 1

Algorithms and Complexity (Core)

The module aims to introduce the concepts of Algorithms and Complexity, providing an understanding of the range of applications where algorithmic solutions are required.

Students will have the opportunity to be introduced to the analysis of time and space efficiency of algorithms; to the key issues in algorithm design; to the range of techniques used in the design of various types of algorithms. Students can also be introduced to relevant theoretical concepts around algorithms and complexity in the lectures, together with a practical experience of implementing a range of algorithms in the workshops.

Computer Architectures (Core)

This module aims to introduce the fundamentals of computer hardware underpinning the key aspects of Computer Science. This knowledge is not only essential for deeper understanding of the governing processes behind computing but also for realising how hardware interacts with software.

By studying Computer Architecture, students can gain greater confidence in their study subject and future benefits when improving their programming skills. The module will study the individual components of a computer system, their function, main characteristics, performance and their mutual interaction. Examples of the practical application of the skills developed in this module are given utilising a range of computing applications, including but not restricted to the domains of Games and Social Computing applications.

Maths for Computing (Core)

This module aims to equip students with mathematical knowledge and skills required to design and develop computer systems and software.

Operating Systems (Core)

In this module students will have the opportunity to study both the theoretical design concepts which underpin all operating systems and, through case studies, the practical implementation techniques of current operating systems. Special attention will be given to shell programming languages and examples, to practically implement concepts and techniques at the basis of the various operating systems.

Problem Solving (Core)

Problems are a natural occurrence in an organisational context and this module aims to introduce students to problem solving from a mixture of theoretical and practical underpinnings.

The module examines the principles of abstraction, decomposition, modelling and representation as a means to frame and characterise problem scenarios, and as tools to understand potential solutions. The module concentrates on problem-solving strategies and in particular the vocabulary through which these strategies are articulated. This type of vocabulary is explored as representational device for capturing organisational behaviour and form.

Programming and Data Structures (Core)

This module aims to introduce the concepts and practice of simple computer programming, with attention paid to the fundamentals that constitute a complete computer program including layout, structure and functionality.

The module aims to extend students' knowledge of computer programming and introduces them to fundamental computing data structures allowing the representation of data in computer programs.

Web Authoring (Core)

This module aims to provide students with the knowledge to design and implement interactive client-side web technologies. Students have the opportunity to learn key concepts in web markup languages; notably the features and capabilities that are part of the HTML5 specification standard including multimedia elements, the canvas element, and local web storage.

Additionally students will have the opportunity to develop technologies that are part of the wider HTML5 family such as CSS3, geolocation, drag and drop, and javascript. A standards driven approach will be adopted throughout the module using web page validation techniques, with emphasis on the importance of separating web page style and structure.

Level 2

Artificial Intelligence (Core)

This module aims to provide a basic introduction to the field of Artificial Intelligence (AI).

The module first considers the symbolic model of intelligence, exploring some of the main conceptual issues, theoretical approaches and practical techniques. The module further explores knowledge-based systems such as expert systems, which mimic human reasoning performance by capturing knowledge of a domain and integrating it to deliver a performance comparable to that of a human practitioner. Modern developments such as artificial neural networks and uncertain reasoning are also covered using probability theory, culminating in a practical understanding of how to apply AI techniques in practice using logic programming.

Database Systems (Core)

In this module students will have the opportunity to explore the fundamental concepts necessary for designing, implementing and using database systems, which require the students to develop a conceptual view of database theory and then transform it into a practical design of a database application.

Alternate design principles for implementing databases for different uses, for example in Social Media or Gaming contexts are also considered.

Group Project (Core)

This module aims to provide students with the experience of working as part of a team on a development project. Students will have the opportunity to produce a set of deliverables relevant to their programme of study, including a finished product or artefact. Final deliverables will be negotiated between the group and their supervisor, the module coordinator will be responsible for ensuring that each project covers the learning outcomes of the module.

Groups are expected to manage their own processes, and to hold regular meetings both with and without their supervisor. Groups will be allocated by the module coordinator and other members of staff. The process of development of the artefact and the interaction and management of group members underpins the assessment of skills in the module.

Human-Computer Interaction (Core)

In this module students will have the opportunity to form an appreciation of the importance of human factors and user-centred approaches in the development of technological systems (analysis, design, implementation and evaluation of technological systems).

Students will be introduced to the physiological, psychological and cognitive issues relevant to human computer interaction and user-interface design.

Networks and Network Systems (Core)

In this module students may consider basic computer communications and networking with an emphasis on the Internet protocol. Internet protocol will be examined as a model for intercommunication in modern network implementations. Additionally students will have the opportunity to explore fundamental design features of a Network Protocol and the need to implement security in the modern Internet.

Object-Oriented Programming (Core)

This module aims to provide a comprehensive analysis of the general principles and practices of advanced programming with respect to software development. Notions and techniques of advanced programming are emphasised in the context of analysis, design and implementation of software and algorithms.

Great importance is placed upon the Object-Oriented paradigm and related concepts applied to algorithm and software development.

Professional Practice (Core)

Professional Practice aims to develop an understanding of the basic cultural, social, legal, and ethical issues inherent in the discipline of computing; and to promote personal professionalism in the workplace. Examples of topics covered include:

  • The special nature of technological ethics.
  • Ethical decision-making and case analysis.
  • Ethics of software development.
  • Legal issues in the field of technology.
  • Codes of computer ethics and professional practice.
  • Globalisation of professionalism.
  • Professional engagement with the job applications process.

Programming Paradigms (Core)

This module provides students with a theoretical overview of the different programming paradigms, specifically Procedural, Object-Oriented, Functional and Logical paradigms.

Comparative techniques are used to explain the differences between them and practical application of example problem scenarios are used to provide the means to contextualise the advantages and disadvantages of each.

Other modules in the programme concentrate the student on procedural and object-oriented programming approaches as their core framework, and the AI module delivers the key aspects of the logical paradigm. This module therefore presents the students with the underpinning theories and principles of functional programming, through mathematical definitions of programme requirements and the application of recursion to create problem solving solution mechanisms.

Level 3

Algorithms for Data Mining (Option)

The module examines the mathematical fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will learn the fundamentals of data science, including basic terminology and concepts, core models, current technology landscape, and topical application scenarios using cloud platforms and open datasets. Students will be introduced to a basic data scientist toolkit that can be applied to design/build data-driven applications, and provide insights into diverse datasets.

Autonomous Mobile Robotics (Core)

The module aims to introduce the main concepts of Autonomous Mobile Robotics, providing an understanding of the range of processing components required to build physically embodied robotic systems, from basic control architectures to spatial navigation in real-world environments.

Students will have the opportunity to be introduced to relevant theoretical concepts around robotic sensing and control in the lectures, together with a practical “hands on” approach to robot programming in the workshops.

Business Intelligence (Option)

Business Intelligence (BI) refers to technologies, applications, and practices for the collection, integration, analysis, and presentation of meaningful and useful information for business purposes.

The purpose of the module is to understand the issues involved in the use and application of these ‘tools’ and how BI might be applied to generate creative and novel insight helping support better business decisions. BI systems are data-driven Decision Support Systems. They provide historical, current, predictive and insightful views of business operations, most often using data gathered from data warehouses. Software elements support reporting, interactive 'slice-and-dice' pivot-table analyses, visualization, and statistical data mining.

Critical Perspectives on Project Management (Option)

The module 'Critical Perspectives on Project Management' aims to explore the practical issues and challenges of putting technology to work.

As technology grows and becomes ever more pervasive, the size, complexity and timescales of related projects grow too. The challenges facing project managers involved in planning, coordinating, directing and implementing technology based projects on-time, to budget and operationally as expected is ever growing. This module aims to develop a critical perspective of project management and uses case based material to develop an understanding about the various challenges project management in this arena presents. Students are encouraged to reflect on the limits of certain forms of rational project management modes in conditions that are more accurately described in terms of uncertainty, complexity, risk and chaos.

Cross-Platform Development (Option)

This module aims to provide students with knowledge on an alternative, and increasingly important, ‘platform agnostic’ approach for mobile development. This approach embraces the use of cross-platform methods by developing applications with a single code base that run efficiently across distinct mobile platforms, with maximum code reuse and interoperability.

Students will have the opportunity to investigate platform-dependent constraints by critiquing the emergent space of cross-platform tools and frameworks that aim to maximise code sharing between mobile platforms, whilst retaining common like-for-like sensor features such as geolocation, camera, storage and push notification’s without compromising performance or overall user experience. Contemporary cross-platform tools will be adopted throughout the module for the creation of applications that bridge multiple mobile platforms.

Cyber Security in Society (Option)

This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social and ethical implications of cyber security.

Data Science Tools and Techniques (Option)

The module introduces the fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will consider the societal, ethical and professional requirements for and uses of data science and be exposed to core concepts and models, the current technology landscape, and topical application scenarios using cloud platforms and open datasets.

Entrepreneurship and Innovation 1 (Option)

This module aims to provide the business context for activities supported by and delivered through computing technologies.

Students may investigate the drivers for modern Electronic Business and consider enterprise applications from a business viewpoint. Students can explore the process of taking a technologically grounded idea, and develop a business case through break-even point to where profitability begins and specify an appropriate web site as the vehicle to deliver the business case. The Entrepreneurial perspective considers business development as a holistic process, students can engage with this notion throughout the module. The module will also draw upon examples and themes from social computing, the importance of which is growing rapidly in importance.

Entrepreneurship and Innovation 2 (Option)

This module aims to build on the principles of 'Entrepreneurship & Innovation 1' and applies formalised methods and approaches in the exploration of specific areas of entrepreneurship and innovation. The module will also investigate the application of social computing principles, game theory and cooperation analysis in the development of an entrepreneurial idea.

Image Processing (Core)

Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection, medical imaging, etc. It is the study of any algorithms that take image as an input and returns useful information as output.

This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from the raw image and interpret the image data — the techniques will be implemented using the mathematical programming language Matlab or OpenCV.

Mobile Computing (Option)

This module provides students with the opportunity to develop knowledge in the specification and development of connected ‘data-driven’ mobile applications, using industry standard tools and guidelines.

Mobile device platforms, such as smartphones can provide a rich development experience with direct access to a number of pervasive sensors such as GPS, camera, proximity, NFC and multiple network connectivity channels. These sensors are used as building blocks for lifestyle-supporting mobile applications in areas such as health, fitness, social, science, and entertainment. Such applications are now seen as part of the everyday fabric of life. Students can learn how to develop topically-themed native mobile applications that consume RESTful web services. Data privacy and security issues are discussed throughout the module.

Parallel Computing (Core)

Parallel Computing is a very important, modern paradigm in Computer Science, which is a promising direction for keeping up with the expected exponential growth in the discipline.

Executing multiple processes at the same time can tremendously increase the computational throughput, not only benefitting scientific computations but also leading to new exciting applications like real-time animated 3D graphics, video processing, physics simulation, etc. The relevance of parallel computing is especially prominent due to availability of modern, affordable computer hardware utilising multi-core and/or large number of massively parallel units.

Project (Computer Science) (Core)

This module provides students with an opportunity to demonstrate their ability to work independently on an in-depth project with an implementation element that builds on their established knowledge, understanding and skills.

Students will normally be expected to demonstrate their ability to apply practical and analytical skills, innovation and/or creativity, and to be able to synthesise information, ideas and practices to provide a problem solution. Self-management is a key concept here, as is the ability to engage in critical self-evaluation.

Software Engineering (Core)

The module covers advanced topics of Software Engineering, focusing on software methodologies, with respect to changes in the software development process including past and present techniques.

Key Software Engineering principles are explored in the context of real world software engineering challenges such as software evolution and reuse. Topics such as advanced testing, verification and validation, critical systems development, re-factoring and design patterns will be covered.

Masters Level

Advanced Artificial Intelligence (Option)

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.

Advanced Programming (Option)

This module aims to 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 can 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 (Option)

This module aims to provide students with advanced concepts of Software Engineering principles and practices. Students can 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 (Option)

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.

Machine Learning (Option)

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.

Mobile and Connected Devices (Option)

This module aims to explore 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 aim to 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 given the opportunity 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)

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.

Level 4

Algorithms for Data Mining (M) (Option)

The module examines the mathematical fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will learn the fundamentals of data science, including basic terminology and concepts, core models, current technology landscape, and topical application scenarios using cloud platforms and open datasets. Students will be introduced to a basic data scientist toolkit that can be applied to design/build data-driven applications, and provide insights into diverse datasets.

Business Intelligence (M) (Option)

Business Intelligence (BI) refers to technologies, applications, and practices for the collection, integration, analysis, and presentation of meaningful and useful information for business purposes. The purpose of the module is to understand the issues involved in the use and application of these ‘tools’ and how BI might be applied to generate creative and novel insight helping support better business decisions. BI systems are data-driven Decision Support Systems. They provide historical, current, predictive and insightful views of business operations, most often using data gathered from data warehouses. Software elements support reporting, interactive 'slice-and-dice' pivot-table analyses, visualization, and statistical data mining.

Working at Masters level, students will have the opportunity to research the area in-depth and produce critical reports of their findings.

Critical Perspectives on Project Management (M) (Option)

The module 'Critical Perspectives on Project Management' aims to explore the practical issues and challenges of putting technology to work. As technology grows and becomes ever more pervasive, the size, complexity and timescales of related projects grow too. The challenges facing project managers involved in planning, coordinating, directing and implementing technology based projects on-time, to budget and operationally as expected is ever growing. This module aims to develop a critical perspective of project management and uses case-based material to develop an understanding about the various challenges project management in this arena presents. Students are encouraged to reflect on the limits of certain forms of rational project management modes in conditions that are more accurately described in terms of uncertainty, complexity, risk and chaos.

Working at Masters level, students can research the area in-depth and produce critical reports of their findings.

Cyber Security in Society (M) (Option)

This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social and ethical implications of cyber security. As a Masters level module students are also encouraged to consider current research in the field of cyber security.

Data Analytics and Visualisation (Option)

This module aims to develop students' understanding of contemporary approaches to data analysis and visualisation. The module places particular emphasis on making sense of large datasets such as those generated from social media interactions or other web sources. It delivers material on the fundamental understanding of human visual perception and the political and persuasive power of data, and develops this alongside the use of standard tools for data collection, processing, manipulation, analysis and visual presentation. The practical role of data analytics and visualisation in media and business contexts is a core thread running through the module.

Data Science Tools and Techniques (M) (Option)

The module introduces the fundamentals of data science: an emergent specialised area of computer science that is concerned with knowledge on ‘BigData’ mining and visualization, including state of the art database platforms, development toolkits, and industrial and societal application scenarios. Students will consider the societal, ethical and professional requirements for and uses of data science and be exposed to core concepts and models, the current technology landscape, and topical application scenarios using cloud platforms and open datasets.

Entrepreneurship and Innovation 1 (M) (Option)

In this module students have the opportunity to investigate the drivers for modern Electronic Business and consider enterprise applications from a business viewpoint. Students can explore the process of taking a technologically grounded idea and develop a business case to the point where profitability begins.

Working at Masters level, students can research the area in-depth and produce critical reports of their findings.

MComp Research Project (Core)

The MComp Research Project is an individual piece of work that expects students to apply and integrate theoretical knowledge and practical skills from the breadth of their experience with computer science sub-disciplines, in order to address a specific research question or questions formulated with support from academic staff.

The form and nature of this project is negotiable, but at MComp Level 4 there are typically three types of Project that are undertaken:

  • Industrial Based Project work (typically engaged with through a work placement)
  • Client-based project delivery (typically with an approved client in either public, private or third sector partners, and with a clearly articulated delivery)
  • A research based project (typically done in conjunction with a member of academic staff in the School and with a clear linkage to research activity of the staff member but which could include collaborative projects with research groups at other Universities)

The student can undertake work that is predominantly relevant to the ongoing research in one of the established research centres within the School of Computer Science. In all cases the Project supervisor will ensure that the study undertaken is suitably grounded within the programme title of each student.

Movement Interfaces (Option)

Recent years have seen growing interest in games interfaces that require movement of the body, and build on the user’s physical skills and abilities; the new dimension introduces a unique set of challenges in the design of games that extends beyond traditional human-computer interaction.

This module aims to provide students with advanced understanding of theoretical and practical concerns related to the design of technology that recognizes, captures and visualizes player movement. A number of inter-disciplinary perspectives on designing for player movement are considered, such as accessibility of games for players with mobility impairments, sports, performance, dance and audience. In addition, students can engage with practical issues related to the design, development and evaluation of movement-based games.

†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.

Special Features

You are taught by academics with specialist experience in areas including computer vision and medical imaging, autonomous systems and robotics, and human-computer interaction. Much of the School's research is internationally recognised, such as a research project into medical imaging by Distinguished Professor of Image Engineering, Nigel Allinson MBE, who was recently awarded a £1.6 million grant from the Wellcome Trust.

Study Visits

Overseas study visits have been a feature of our courses in recent years. Visits aim to provide students with a unique insight into games development issues in overseas territories. In 2015, students had the opportunity to attend a summer school in China with our partner, Sichuan University, and work alongside students from a number of countries to develop skills in Mobile App Development as well as having free time to visit the local panda breeding centre (the total cost for each student was approximately £300, based on 2015 costs).

Placements

This degree is optionally available in a sandwich mode variant. If students choose the sandwich placement option, they take a year out in industry between years two and three, where they can gain invaluable industrial experience. Students are supported throughout their placement, which can be overseas. There are opportunities to take shorter work placements and to be involved in systems development projects for real clients.

Students must apply specifically for the sandwich variant; if they join via the standard route we may not allow a transfer to the sandwich variant, as places are limited.

Placement Year

When students are on an optional placement in the UK or overseas or studying abroad, they will be required to cover their own transport and accommodation and meals costs. Placements can range from a few weeks to a full year if students choose to undertake an optional sandwich year in industry.

Students are encouraged to obtain placements in industry independently. Tutors may provide support and advice to students who require it during this process.

Student as Producer

Student as Producer is a model of teaching and learning that encourages academics and undergraduate students to collaborate on research activities. It is a programme committed to learning through doing.

The Student as Producer initiative was commended by the QAA in our 2012 review and is one of the teaching and learning features that makes the Lincoln experience unique.

Facilities

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.

At Lincoln, we constantly invest in our campus as we aim to provide the best learning environment for our undergraduates. 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.

View our campus pages [www.lincoln.ac.uk/home/campuslife/ourcampus/] to learn more about our teaching and learning facilities.

Career Opportunities

This degree aims to equip graduates with the mathematical, analytical and problemsolving skills that make them well-placed for computer and technology-related roles across a range of sectors. Recent graduates have secured roles at GCHQ and major companies including IBM, PricewaterhouseCoopers and G4S. Some graduates may wish to pursue academic careers and study at postgraduate level.

Careers Service

The University Careers and Employability Team offer qualified advisors who can work with students to provide tailored, individual support and careers advice during their time at the University. As a member of our alumni we also offer one-to-one support in the first year after completing a course, including access to events, vacancy information and website resources; with access to online vacancies and virtual resources for the following two years.

This service can include one-to-one coaching, CV advice and interview preparation to help you maximise our graduates 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 for further information. [http://www.lincoln.ac.uk/home/campuslife/studentsupport/careersservice/]

Additional Costs

For each course students may find that there are additional costs. These may be with regard to the specific clothing, materials or equipment required, depending on their subject area. Some courses provide opportunities for students to undertake field work or field trips. Where these are compulsory, the cost for the travel, accommodation and meals may be covered by the University and so is included in the fee. Where these are optional students will normally (unless stated otherwise) be required to pay their own transportation, accommodation and meal costs.

With regards to text books, the University provides students who enrol with a comprehensive reading list and our extensive library holds either material or virtual versions of the core texts that students are required to read. However, students may prefer to purchase some of these for themselves and will therefore be responsible for this cost. Where there may be exceptions to this general rule, information will be displayed in a section titled Other Costs below.

Related Courses

The MComp Computer Science degree is a four-year, integrated Master's degree is designed to give the experience, skills and knowledge to design and develop a variety of software and hardware computing solutions for real-world problems.
Electrical engineering is essential to the modern world, encompassing everything from energy and automation through to communications and transport. The BEng (Hons) Electrical Engineering programme is designed to equip students with the skills to succeed as the engineers of the future.
The BSc (Hons) Games Computing degree at Lincoln aims to develop the skills and attributes required for roles in the games and entertainment industries, including mobile, social media and console game development. Students can also learn skills relevant to work in broader technological environments.
The MComp is a four-year degree programme which enhances and extends the equivalent BSc (Hons) programme. It provides the opportunity to study a range of modules at Master’s level and to complete a substantive project in an area of specific personal interest. Studying at Master’s level enables you to both deepen and broaden your knowledge and understanding. This can provide you with a stronger CV and may give you a distinct edge in the job market.
This research-informed BSc (Hons) Mathematics degree aims to provide a fundamental education in the fascinating field of mathematics, including pure and applied mathematics. Students have opportunities to work alongside academic staff on challenging projects, which could contribute to academic research or collaboration with industry.
The research-informed MMath Mathematics degree aims to provide a fundamental education in mathematics, including pure and applied mathematics. There will be opportunities for students to develop high-level mathematical and problem-solving skills and to apply these in a variety of contexts. Students will also have the chance to work alongside fellow undergraduates and academic staff on projects.

Tuition Fees

2017/18UK/EUInternational
Full-time £9,250 per level £14,500 per level
Part-time £77.00 per credit point  N/A
Placement (optional) Exempt Exempt

 

2018/19UK/EUInternational
Full-time £9,250 per level £15,600 per level
Part-time £77.00 per credit point  N/A
Placement (optional) Exempt Exempt

The University undergraduate tuition fee may increase year on year in line with government policy. This will enable us to continue to provide the best possible educational facilities and student experience.

In 2017/18, fees for all new and continuing undergraduate UK and EU students will be £9,250.

In 2018/19, fees may increase in line with Government Policy. We will update this information when fees for 2018/19 are finalised.

Please note that not all courses are available as a part-time option.

For more information and for details about funding your study, please see our UK/EU Fees & Funding pages or our International funding and scholarship pages. [www.lincoln.ac.uk/home/studyatlincoln/undergraduatecourses/feesandfunding/] [www.lincoln.ac.uk/home/international/feesandfunding/]

The University intends to provide its courses as outlined in these pages, although the University may make changes in accordance with the Student Admissions Terms and Conditions [www.lincoln.ac.uk/StudentAdmissionsTermsandConditions].