Program Overview

MSci Mathematics and Data Science - 2026 entry

Overview

The MSci Mathematics and Data Science degree combines traditional mathematical techniques with exciting contemporary applications in the field of data science. This innovative and interdisciplinary degree allows you to use mathematics to develop a deeper understanding of the processes behind data manipulation. Designed in partnership with industry, this degree is aimed at those interested in following a career in data science or wishing to progress into further study, such as a PhD.

Entry Requirements

• Typical offer: A levels: AAA, IB: 36/666, BTEC: DDD
• Contextual offers: A-Level: ABB, IB: 32/655, BTEC: DDM
• Specific subject requirements: GCE A-Level Maths grade A, HL6 in Mathematics (Analysis and Approaches)
• GCSE: Grade 4/C in GCSE English language
• Access to HE: 30 L3 credits at Distinction Grade and 15 L3 credits at Merit grade
• T-Level: T-Levels not accepted
• Other accepted qualifications: View other accepted qualifications
• English language requirements: International students need to show they have the required level of English language to study this course. The required test scores for this course fall under Profile B2.

Course Content

Year 1

• Compulsory modules:
  • ECM1400: Programming (15 credits)
  • ECM1410: Object-Oriented Programming (15 credits)
  • MTH1002: Mathematical Methods (30 credits)
  • MTH1004: Probability, Statistics and Data (30 credits)
  • COM1011: Fundamentals of Machine Learning (15 credits)
  • ECM1407: Social and Professional Issues of the Information Age (15 credits)

Year 2

• Compulsory modules:
  • MTH2003: Differential Equations (15 credits)
  • MTH2004: Vector Calculus and Applications (15 credits)
  • MTH2006: Statistical Modelling and Inference (30 credits)
  • COM2011: Machine Learning and Data Science (15 credits)
  • COM2020: Team Project (15 credits)
• Optional modules:
  • COM2014: Computational Intelligence (15 credits)
  • Free Choice Elective (30 credits)

Year 3

• Compulsory modules:
  • ECM3401: Individual Literature Review and Project (45 credits)
• Optional modules:
  • COM3021: Data Science at Scale (15 credits)
  • COM3031: Probabilistic Machine Learning (15 credits)
  • Select 4 modules (60 credits) from:
    • MTH3001: Theory of Weather and Climate (15 credits)
    • MTH3006: Mathematical Biology and Ecology (15 credits)
    • MTH3007: Fluid Dynamics (15 credits)
    • MTH3008: Partial Differential Equations (15 credits)
    • MTH3019: Mathematics: History and Culture (15 credits)
    • MTH3022: Graphs, Networks and Algorithms (15 credits)
    • MTH3024: Stochastic Processes (15 credits)
    • MTH3028: Statistical Inference: Theory and Practice (15 credits)
    • MTH3030: Mathematics of Climate Change (15 credits)
    • MTH3041: Bayesian statistics, Philosophy and Practice (15 credits)
    • MTH3042: Integral Equations (15 credits)
    • MTH3045: Statistical Computing (15 credits)
  • Select up to 1 module (0-15 credits) from:
    • EMP3001: Commercial and Industrial Experience (15 credits)
    • Free choice electives (30 credits)

Final Year

• Compulsory modules:
  • ECMM427: Group Development Project (30 credits)
• Optional modules:
  • ECMM428: Individual Research Project (30 credits)
  • Select 60 credits:
    • MTHM009: Advanced Topics in Mathematical & Computational Biology (15 credits)
    • MTHM017: Advanced Topics in Statistics (15 credits)
    • MTHM018: Dynamical Systems and Chaos (15 credits)
    • MTHM019: Fluid Dynamics of Atmospheres and Oceans (15 credits)
    • MTHM023: Modelling the Weather and Climate (15 credits)
    • MTHM030: Waves, Instabilities and Turbulence (15 credits)
    • MTHM031: Magnetic Fields and Fluid Flows (15 credits)
    • MTHM033: Statistical Modelling in Space and Time (15 credits)
    • MTHM045: Space Weather and Plasmas (15 credits)
    • MTHM048: Ergodic Theory (15 credits)
    • Any other level 4 Mathematics module(s) (15 credits)

Fees

• Tuition fees for 2025 entry: UK students: £9,535 per year, International students: £29,800 per year
• Scholarships: The University of Exeter has many different scholarships available to support your education, including £5 million in scholarships for international students applying to study with us in the 2025/26 academic year.

Learning and Teaching

• Assessment: All our degrees involve a combination of teaching methods, including lectures, seminars, examples classes, workshops and tutorials.
• Private study and support: In addition to lectures and seminars, you should spend about 20 hours per week in private study.
• Project and computer work: There are modules at all levels that involve project work and report writing, and the final year project is a major piece of research and writing that allows you to go into depth for a specific area under the guidance of a member of academic staff.

Your Future

• Career paths: The broad-based skills acquired during your degree will give you an excellent grounding for a wide variety of careers, not only those related to Mathematics but also in wider fields.
• Related courses:
  • Mathematics MMath
  • Mathematics and Data Science BSc
  • Computer Science MSci
  • Natural Sciences MSci
  • Computer Science and Mathematics MSci
  • Mathematics with Accounting BSc