MSci
MSci Computer Science and Mathematics
Taught by discipline specialists and informed by industry, this MSci brings together the complementary fields of computer science and mathematics. It offers opportunities to specialise and to engage with the cutting-edge research being carried out in both departments.
How to apply Apply via UCAS
Course details
Start date
Degree Type
MSci
UCAS Code
G425
Course length
4 years full-time
Typical offer
A*AA
Tuition Fees
- Home (Full-time): £9,535 per year
- Overseas (Full-time): £33,250 per year
Overview
The MSci Computer Science and Mathematics degree is meticulously crafted to equip students with the foundational knowledge and practical skills required to thrive in the constantly changing data-driven workplace. In our rapidly evolving world, the field of computer science stands as a driving force behind transformative technological breakthroughs that have reshaped our lives for the better. The skills demanded by today's dynamic tech sector demand a strong knowledge in mathematical fundamentals, statistics, and machine learning. During the first two years you will follow the same course structure as the BSc with an equal balance of Computer Science and Mathematics to ensure that the programme provides students with the essential foundation. From the third year, the MSci introduces a wider range of modules and an advanced project in the final year. Cap off your academic journey with a choice between undertaking an advanced project, where you tackle a theoretical area or an applied problem in-depth , or our distinctive interdisciplinary enterprise module where you can delve into an area that resonates with your passions and leverages the skills honed within the course. You will be taught by passionate researchers with diverse areas of expertise such as artificial intelligence, data science, fundamental algorithms, statistical uncertainty, statistical uncertainty, applied statistics for large-scale applications and applied algebra. The final-year advanced project is an opportunity to fully engage with the cutting-edge research being carried out in the departments. State-of-the-art facilities further enhance the learning experience, providing students with access to cutting-edge resources and opportunities to engage in innovative research projects.
Course details
Start date
Degree Type
MSci
UCAS Code
G425
Course length
4 years full-time
Typical offer
A*AA
Tuition Fees
- Home (Full-time): £9,535 per year
- Overseas (Full-time): £33,250 per year
What you'll study
The Year 1 curriculum provides a foundation in the fundamentals of computer science, pure mathematics, statistics, and probability providing robust groundwork for advanced study in subsequent years. Year 2 allows students to embark on an exploration of a diverse array of innovative technological applications. At the same time, this can be underpinned with a deep mathematical grounding in statistics and machine learning to provide the foundation on their academic journey for more advanced topics in statistics, artificial intelligence and data science or an alternative grounding in abstraction with applications in theoretical computer science. The flexible structure, coupled with an array of optional modules, empowers you to tailor your academic trajectory in alignment with your evolving interests. Whether completing the programme in three years, opting for a placement year, or embarking on a year abroad, the choice is yours.
Core modules
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Algorithms and Data Structures
introduces the theory and practice of problem-solving in computing through the development of algorithms and their associated data structures, for common computer science problems. Content included machine modelling, control flow structures and analysis of algorithms.
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Calculus
builds on ideas of differentiation and integration in A level mathematics. The module begins with functions of a single variable before moving on to functions of several variables. Topics include methods of solving ordinary and partial differential equations, and an introduction to Taylor series, Fourier series and Fourier transforms.
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Computational Thinking
explores the breadth of computer science and the ways in which the different topics are linked. You will learn the importance of computation and computational thinking in the modern world and the impact it has on technology advances in different settings.
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Linear Algebra
presents mathematical ideas, techniques in linear algebra and develops the geometric intuition and familiarity with vector methods you will need for more challenging material later in the course.
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Probability
introduces mathematical ideas on probability in preparation for more demanding material later in the course. The module builds problem solving skills through the exploration of a mathematical subject of relevance to the real-world (applied) that is based on rigorous mathematical foundations (pure).
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Statistics
introduces frequentist and Bayesian approaches and demonstrates the relevance of these principles and procedures using real problems. This introductory module lays the foundations for all subsequent study of statistics.
Optional modules
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In recent years, optional modules have included: Computer SystemsProgramming.
Optional modules
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In recent years, optional modules have included: Theory of ComputationProgramming ParadigmsArtificial IntelligenceData ScienceProbabilityStatistical ModellingStatistical InferenceData Science and Statistical ComputingAlgebra
Core modules
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Project Preparation
You will work on essential research skills including researching a topic, writing, presenting, and begin preparation for the final-year Advanced Project in an area of your choice.
Optional modules
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In recent years, optional modules have included: Algorithmic Game TheoryBioinformaticsDeep LearningHuman-AI Interaction DesignRecommender SystemsReinforcement LearningNatural Computing AlgorithmsAdvanced Statistical ModellingBayesian Computation and ModellingCryptography and CodesDecision TheoryMachine Learning and Neural NetworksMathematical FinanceOperations ResearchStochastic ProcessesScience Enterprise
Core modules
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Advanced Project in Computer Science
Either the or Mathematics Project Your final-year project is a detailed and critical examination of a relevant area of computer science, mathematics or statistics. It is possible that the resulting research might be published in a journal or at a conference, possibly as a prelude to higher level studies.
Optional modules
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In recent years, optional modules have included: Advanced AlgorithmsApplied CryptographyBlockchain and CryptocurrenciesCoding and Information TheoryLearning AnalyticsNatural Language ProcessingQuantum ComputingRandomised Algorithms and Probabilistic MethodsRepresentation TheoryTopics in CombinatoricsHigh-Dimensional StatisticsUncertainty QuantificationNonparametric StatisticsDeep Learning and Artificial Intelligence
Learning
Learning is centred in a modern purpose-built space containing lecture and seminar rooms, open-plan workspace, breakout areas, labs, and computer rooms. For most modules, you will attend lectures supported by small-group tutorials, problem classes, homework problems, written and oral presentations, and individual projects. You will also take part in computer practicals where you put into practice what you learn in lectures. We place great emphasis on high-quality small-group teaching, which includes one-on-one attention from your academic advisors, self-directed learning to develop your critical thinking skills, and collaborative working with other students. As you move into Years 3 and 4 the focus on self-directed learning and independent research increases as you begin to prepare for professional or postgraduate life.Assessment
Some modules are assessed entirely through coursework (which may involve problem solving exercises, practical work and assignments) and others by examination, while others are assessed using a combination of methods. The final-year advanced project is an opportunity to bring your learning to a project of your choice. The project is a significant piece of independent research completed under the supervision of an academic from your chosen specialism.Entry requirements
Fees & Funding
Choose which fees you want to see:
Home / Island students
£9,535 per year
International / EU Students
£33,250 per year
Home / Island students
Part Time - £ per year
International / EU Students
Part Time - £ per year
The tuition fees shown are for one complete academic year of study, are set according to the academic year of entry, and remain the same throughout the duration of the programme for that cohort (unless otherwise stated).
Find out moreDepartment Information
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The Department of Natural Sciences offers Joint Honours science degrees and personalized self-built degree programmes. The degrees are taught by discipline specialists and leverage Durham's extensive, research-led education. They provide significant flexibility, enabling students to tackle challenges from various perspectives. Additionally, most students have the option to transfer to a Single Honours degree after the first year if they wish. Approximately 800 students are enrolled in the Department, which is overseen by a Director and Deputy Directors. They collaborate closely with senior colleagues from contributing departments with the aim of providing degrees that offer the same depth and experience as Single Honours programmes, but with greater disciplinary diversity and a broader skill set, enhancing employability. For more information see our department pages.
Read moreFacilities
You will have access to a wide range of facilities across multiple departments. Facilities will depend on the subject specialism but include laboratories, libraries, project spaces, lecture theatres, study and networking spaces as well as shared social spaces. You will also benefit from excellent IT facilities including Learn Ultra, Durham’s virtual learning environment. You will have access to up to 1.6 million printed books, 25,000 eJournals and over 850,000 eBooks in the main library. Most departments are close to the historic centre of Durham which is a UNESCO World Heritage site.
Find out more -
Career Opportunities
HESA Graduate Outcomes Survey. The survey asks leavers from higher education what they are doing 15 months after graduation. Further information about the Graduate Outcomes survey can be found here www.graduateoutcomes.ac.uk
Employability
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