This programme has been accredited by the The Institute of Mathematics and its Applications (IMA).
The BSc (Hons) Mathematics and Computer Science degree aims to provide a broad education in applied and pure mathematics, coupled with the equally broad range of skills provided by computer science.
With digital technologies driving advances in all aspects of the modern world, there is growing demand for graduates with these combined skills, in a wide range of sectors. Mathematics is at the foundation of many different areas, and the joint aspect of this programme provides students with the opportunity to access a higher level of understanding in both fields, as a combined effort.
This programme meets the educational requirements of the Chartered Mathematician designation, (awarded by the Institute of Mathematics and its Applications), when it is followed by subsequent training and experience in employment to obtain equivalent competences to those specified by the Quality Assurance Agency (QAA) for taught masters degrees.
How You Study
The School of Mathematics and Physics is dedicated to achieving excellence in research and aims to provide a friendly, approachable culture for students to join.
The course is taught via lectures, problem solving classes, computer based classes and seminars. There is an average of 12 hours of contact study per week (additional student-managed independent study is required).
In the first year students have the chance to benefit from an additional three hours per week of problem solving tutorials.
During the first year of the programme, the School of Mathematics and Physics also runs a tutor system, providing one hour weekly tutor sessions in small groups.
Contact Hours and Independent Study
Contact hours may vary for each year of your degree. However, remember that you are engaging in a full-time degree; so, at the very least, you should expect to undertake a minimum of 37 hours of study each week during term time and you may undertake 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.
Please see the Unistats data, using the link at the bottom of this page, for specific information relating to this course in terms of course composition and delivery, contact hours and student satisfaction.
How You Study
The University of Lincoln's policy on assessment feedback aims to ensure that academics will return in-course assessments to you promptly – usually within 15 working days after the submission date (unless stated differently above).
Methods of Assessment
The way you 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.
For a comprehensive list of teaching staff, please see our School of Mathematics and Physics Staff Pages.
Entry Requirements 2017-18
GCE Advanced Levels: BBC, to include a grade B from A Level Maths.
International Baccalaureate: 29 points overall, with 5 points at Higher Level in Maths.
In addition, applicants must have a minimum of three GCSEs (or the equivalent) at grade C or above, to include Maths and English.
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 email@example.com.
This module begins with refreshing some of the material from A-Level Maths, such as the binomial theorem and division of polynomials. The main part of the module is a systematic study of general systems of simultaneous linear equations and their solutions. Vectors and matrices are introduced in order to describe the properties of these systems and solutions, and complete answers are obtained to such questions as whether a solution exists and if so how many solutions there are.
Algorithms and Complexity
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.
This module focuses on the concepts of the derivative and the Riemann integral, which are indispensable in modern sciences.
Two approaches are used: both intuitive-geometric, and mathematically rigorous, based on the definition of continuous limits. Important results are the Mean Value Theorem, leading to the representation of some functions as power series (the Taylor series), and the Fundamental Theorem of Calculus which establishes the relationship between differentiation and integration. Further calculus tools are explored, such as the general properties of the derivative and the Riemann integral, as well as the techniques of integration. In this module, students may deal with many 'popular' functions used throughout mathematics.
This module describes vector spaces and matrices.
Matrices are regarded as representations of linear mappings between vector spaces. Eigenvalues and eigenvectors are introduced, which lead to diagonalization and reduction to other canonical forms. Special types of mappings and matrices (orthogonal, symmetric) are introduced. Applications of linear algebra to geometry of quadratic surfaces are explored.
Probability and Statistics
This module begins with an introduction of a probability space, which models the possible outcomes of a random experiment. Basic concepts such as statistical independence and conditional probability are introduced, with various practical examples used as illustrations. Random variables are introduced, and certain well-known probability distributions are explored.
Further study includes discrete distributions, independence of random variables, mathematical expectation, random vectors, covariance and correlation, conditional distributions and the law of total expectation. The ideas developed for discrete distributions are applied to continuous distributions.
Probability theory is a basis of mathematical statistics, which has so many important applications in science, industry, government and commerce. Students will have the opportunity to gain a basic understanding of statistics and its tools. It is important that these tools are used correctly when, for example, the full picture of a problem (population) must be inferred from collected data (random sample).
Programming and Data Structures
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.
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.
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.
Transmission of data may mean sending pictures from the Mars rover, streaming live music or videos, speaking on the phone, answering someone's question “do you love me?”. Problems arise if there are chances of errors creeping in, which may be catastrophic (say, receiving “N” instead of “Y”).
Coding theory provides error-correcting codes, which are designed in such a way that errors that occur can be detected and corrected (within certain limits) based on the remaining symbols. The problem is balancing reliability with cost and/or slowing the transmission. Students will have the opportunity to study various types of error-correcting codes, such as linear codes, hamming codes, perfect codes, etc., some of which are algebraic and some correspond to geometrical patterns.
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.
Calculus techniques already provide solutions of simple first-order differential equations. Solution of second-order differential equations can sometimes be achieved by certain manipulations. Students may learn about existence and geometric interpretations of solutions, even when calculus techniques do not yield solutions in a simple form. This is a part of the existence theory of ordinary differential equations and leads to fundamental techniques of the asymptotic and qualitative study of their solutions, including the important question of stability. Fourier series and Fourier transform are introduced.
This module provides an introduction to the classical second-order linear partial differential equations and techniques for their solution. The basic concepts and methods are introduced for typical partial differential equations representing the three classes: parabolic, elliptic, and hyperbolic.
This module aims to provide students with the experience of working as part of a team on a project.
Students will have the opportunity to produce a set of deliverables relevant to their programme of study. 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 topic under study and the interaction and management of group members underpins the assessment of skills in the module.
Industrial and Financial Mathematics
Students have the opportunity to learn how mathematics is applied to modern industrial problems, and how the mathematical apparatus finds applications in the financial sector.
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.
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.
Advanced Topics of Mathematics and Mathematics Seminar (Option)
The module will cover several advanced topics of modern mathematics. The choice of the topics will be governed by the current research interests of academic staff and/or visiting scientists.
Students will also have the opportunity to participate in mathematics research seminars.
Autonomous Mobile Robotics (Option)
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.
Fluid Dynamics (Option)
This module gives a mathematical foundation of ideal and viscous fluid dynamics and their application to describing various flows in nature and technology.
Students are taught methods of analysing and solving equations of fluid dynamics using analytic and most modern computational tools.
Group Theory (Option)
Symmetry, understood in most broad sense as invariants under transformations, permeates all parts of mathematics, as well as natural sciences. Groups are measures of such symmetry and therefore are used throughout mathematics.
Abstract group theory studies the intrinsic structure of groups. The course begins with definitions of subgroups, normal subgroups, and group actions in various guises. Group homomorphisms are introduced and the related isomorphism theorems are proved. Sylow p-subgroups are introduced and the three Sylow theorems are proved. Throughout, symmetry groups are used as examples.
Image Processing (Option)
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.
Mathematics Pedagogy (Option)
This module is designed to provide students with an insight into the teaching of Mathematics at secondary school level and does this by combining university lectures with an experience of a placement in a secondary school Mathematics department.
The module aims to provide students with an opportunity to engage with cutting-edge maths education research and will examine how this research impacts directly on classroom practice. Students will have the opportunity to gain an insight into some of the key ideas in Mathematics pedagogy and how these are implemented in the school Mathematics lessons and will develop an understanding about the barriers to learning Mathematics that many students experience.
Methods of Mathematical Physics (Option)
The module aims to equip students with methods to analyse and solve various mathematical equations found in physics and technology.
Mobile Computing (Option)
This module aims to provide students with knowledge in the design, development, and evaluation of cloud-connected mobile applications using industry standard tools and guidelines.
Mobile device platforms – smartphones - 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 will learn how to develop topically-themed mobile applications that consume cloud-connected web services. Data privacy and security issues are discussed throughout the module. Access to smartphone technologies globally, feature phone vs. smartphone comparison and users of such devices, access constraints to data and other services - such as local government and banking.
Numerical Methods (Option)
The module aims to equip students with knowledge of various numerical methods for solving applied mathematics problems, their algorithms and implementation in programming languages.
Parallel Computing (Option)
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.
This is a double module in which a student can undertake a project under supervision of a research-active member of staff. The project can be undertaken at an external collaborating establishment. Projects will be offered to students in a wide range of subjects, which will be assigned with account for students' individual preferences and programme of their studies.
This module provides students with an opportunity to demonstrate their ability to work independently on an in-depth project with a computer implementation element of mathematically relevant problem. 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.
Software Engineering (Option)
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.
Tensor Analysis (Option)
This module introduces tensors, which are abstract objects describing linear relations between vectors, scalars, and other tensors. The module aims to equip students with the knowledge of tensor manipulation, and introduces their applications in modern science.
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.
Research is a critical part of the academic environment at the University of Lincoln, and as one of our students you can expect to be taught by research academics in the field. Under our “student as producer” initiative (see below) you will be expected to contribute to new knowledge yourself. Research will form a part of your study from your first year in a variety of ways such as individual and team projects, and will culminate in the final year project.
When you are on an optional placement in the UK or overseas or studying abroad, you will be required to cover your 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.
The University is developing new purpose-designed facilities for the School of Mathematics and Physics at the heart of its Brayford Pool campus.
At Lincoln, we constantly invest in our campus as we aim to provide the best learning environment for our undergraduates. Whatever your area of study, the University strives to ensure students have access to specialist equipment and resources, to develop the skills, which you may need in your future career.
View our campus pages [www.lincoln.ac.uk/home/campuslife/ourcampus/] to learn more about our teaching and learning facilities.
Mathematics and Computer Science graduates may have a broad knowledge and skill base that is suitable for computer and IT-related posts across a range of sectors, as well as research and analytical roles. Furthermore, professional mathematicians can find routes into occupations such as science, education, consultancy, finance, business and industry in the UK, Europe and even further afield. Graduates are in demand with employers and are often sought after for their additional mathematics, analytical and problem-solving skills.
The University Careers and Employability Team offer qualified advisors who can work with you to provide tailored, individual support and careers advice during your time at the University. As a member of our alumni we also offer one-to-one support in the first year after completing your course, including access to events, vacancy information and website resources; with access to online vacancies and virtual and website resources for the following two years.
This service can include one-to-one coaching, CV advice and interview preparation to help you maximise your future opportunities.
The service works closely with local, national and international employers, acting as a gateway to the business world.
Visit our Careers Service pages for further information. [http://www.lincoln.ac.uk/home/campuslife/studentsupport/careersservice/]
For each course you may find that there are additional costs. These may be with regard to the specific clothing, materials or equipment required, depending on your course. Some courses provide opportunities for you to undertake field work or field trips. Where these are compulsory, the cost for the travel, accommodation and your meals may be covered by the University and so is included in your fee. Where these are optional you will normally (unless stated otherwise) be required to pay your own transportation, accommodation and meal costs.
With regards to text books, the University provides students who enrol with a comprehensive reading list and you will find that our extensive library holds either material or virtual versions of the core texts that you are required to read. However, you may prefer to purchase some of these for yourself and you will be responsible for this cost. Where there may be exceptions to this general rule, information will be displayed in a section titled Other Costs below.
|Full-time||£9,250 per level||£14,500 per level|
|Part-time||£77.09 per credit point†|
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, subject to final confirmation from government, there will be an inflationary adjustment to fees to £9,250 for new and returning UK/EU students. In 2018/19 there may be an increase in fees in line with inflation.
We will update this information when fees for 2017/18 are finalised.
†Please note that not all courses are available as a part-time option.