Mathematics with Data Science at City, University of London - UCAS

Course options

Course summary

This MSci, combining practical skills in both mathematics and data science, serves as a benchmark qualification recognised by employers looking for graduates with strong analytical and data skills and capable of advanced quantitative analysis and critical thinking, and opens doors to further study in a variety of disciplines. Whether you are managing an investment portfolio, encrypting financial transactions or constructing a machine-learning algorithm to identify hidden patterns in your customer database you will likely be doing it through a combination of Mathematics and Data Science methods. The Mathematics with Data Science MSci provides comprehensive training for the widest range of careers, because virtually all industries need graduates with skills in these disciplines. The confidence and knowledge you gain at City will open doors to a rewarding and satisfying career.

  • Understand the universal nature of mathematics as a discipline that knows no borders or language barriers
  • Master a wide range of mathematical and data science topics and techniques, such as calculus, probability and machine learning
  • Learn to implement sophisticated algorithms, data mining techniques artificial intelligence with real world applications.
  • Boost your employability with an optional paid one-year work placement – past students have secured placements at organisations such as Axa, Barclays, Bloomberg, Disney, Microsoft, Toyota and Warner Music
  • Take special career development modules to understand mathematics’ essential role across all industries and the opportunities available to you.
Explore your interests through a research project chosen from a wide variety of mathematical topics – past projects have included everything from life-saving mathematics in medical imaging, to wallpaper patterns.


This four-year MSci Mathematics with Data Science degree is focused on pure mathematics with real applications. As you progress, you will have increasing choice and flexibility about what you choose to study. Year 1 consists of modules that make up 125 credits. All modules are core. -Functions, Vectors and Calculus (30 credits) -Algebra (15 credits) -Linear Algebra (15 credits) -Introduction to Probability and Statistics (15 credits) -Logic and Set Theory (15 credits) -Number Theory and Cryptography (15 credits) -Introduction to Modelling (15 credits) -Skills, Careers and Employability Analysis for Mathematics students (5 credits) Year 2 consists of modules that make up 125 credits. -Programming and Data Science for the Professions (15 credits) -Real and Complex Analysis (30 credits) -Vector Calculus (15 credits) -Sequences and Series (15 credits) -Decision Analysis (15 credits) -Applied Mathematics (15 credits) -Numerical Mathematics (15 credits) -Professional Development and Employability (5 credits) -Applications of Probability and Statistics (15 credits) Year 3 consists of modules that make up 120 credits. -Codes (15 credits) -Techniques for Data Science (15 credits) -Group project (15 credits) -Principles of Data Science (15 credits) Introduction to Artificial Intelligence (15 credits) -Machine Learning (15 credits) -Differential Equations (30 credits) -Advanced Complex Analysis (15 credits) -Stochastic Models (15 credits) -Operational Research (15 credits) -Probability and Statistics 2 (30 credits) -Graph Theory (15 credits) -Game Theory (15 credits) -Dynamical Systems (15 credits) -Introduction to the Mathematics of Fluids (15 credits) -Introduction to Mathematical Physics -Mathematical Processes for Finance (15 credits) -Groups and Symmetry (15 credits) -Mathematical Biology (15 credits) Year 4 -MSci Project (30 credits) -Mathematics: algorithms, computation and experimentation (15 credits) -Machine Learning (15 credits) -Data Visualisation (15 credits) -Deep Learning (15 credits) -Principles of Data Science (15 credits) -Introduction to Artificial Intelligence (15 credits) -Mathematics for Quantum Computing (15 credits) -The Mathematics of Information (15 credits) -Forecasting (15 credits) -Perturbation Methods (15 credits) -Game Theory (15 credits) -Graph Theory (15 credits) -Dynamical Systems (15 credits)

Assessment method

Assessment is based on examination and coursework. Marks are weighted in a 1:3:6:6 ratio for the four years of study to produce an overall aggregate. Types of assessment

  • Set exercises or coursework, which you take home and complete with the aid of your notes
  • Formal unseen written examinations every year
  • Class or online tests
  • Group assessments, such as written reports, also form the basis of assessment for some modules.
  • There is a project in the fourth year. Also, a small number of modules require students to give presentations.
Feedback on assessment You will normally be provided with feedback within three weeks of the submission deadline or assessment date. This would normally include a provisional grade or mark. For end-of-module examinations or an equivalent significant task (e.g. an end of module project), feedback will normally be provided within four weeks. The timescale for feedback on final-year projects or dissertations may be longer.

How to apply

Application codes

Course code:
Institution code:
Campus name:
City, University of London
Campus code:

Points of entry

The following entry points are available for this course:

  • Year 1

Entry requirements

Qualification requirements

Contextual offers We apply a contextual admissions process for UK undergraduate applicants who have been in care or are the first in their family to enter Higher Education. Those who are eligible may receive a conditional offer with reduced entry requirements, typically two grades lower for A-levels and one grade (or eight tariff points) for BTEC or mixed qualifications. Read our contextual admissions policy for eligibility criteria and further information. Mixed qualifications Typically the only scenario where we make conditional offers expressed as UCAS tariff points is when an applicant presents mixed qualifications, most typically a combination of A-levels and a BTEC qualification. In this instance, we may make a tariff point offer to present the applicant with more flexibility on equivalencies. In this case, please be aware that we may still ask for a specific score across certain qualifications and subjects. E.g. 'This offer is conditional on you achieving 128 tariff points. This must include A-level Mathematics at grade B.' Subject exclusions We do not accept General Studies and Critical Thinking. These subjects will not be included in any conditional offer we make. Extended Project Qualification (EPQ) We welcome applications from students who are completing relevant EPQ Projects. Whilst we recognise the value of these projects in preparing students for independent learning at university, the EPQ is unlikely to form part of any conditional offer we make. The EPQ will also not lower the specifics of any conditional offer we choose to make. We will consider the EPQ as part of the holistic assessment of the application and it could be used to form part of our final decision at Confirmation stage. AS levels We recognise that there will be differences of opportunity varying by school and college. As not all students will have the opportunity to sit AS Level exams, it is unlikely we will include AS Level grades in any offer we choose to make. Where students have completed an AS Level subject, we will consider this as part of the holistic assessment of the application and it could be used to form part of our final decision at Confirmation stage. University preparation programmes If you do not qualify for direct entry, you may wish to take a foundation programme first. These programmes are designed to prepare students for entry to City's undergraduate courses. Access to Higher Education We welcome Access course applications from 'mature' students. These applicants will be considered on the basis of their own merits. Please be aware that Access students are often asked for further information to supplement their application, this is normally in the form of a questionnaire.

English language requirements

If your first language is not English, we will require evidence of English language proficiency. Minimum requirements are: IELTS: 6.0 overall with a minimum of 6.0 in each component. GCSE: A minimum of grade 4 (C) in English. PTE Academic: 59 overall with a minimum of 59 in each component.

Student Outcomes

Operated by the Office for Students

There is no data available for this course. For further information visit the Discover Uni website.

Fees and funding

Tuition fees

England £9250 Year 1
Northern Ireland £9250 Year 1
Scotland £9250 Year 1
Wales £9250 Year 1
EU £19370 Year 1
International £19370 Year 1

Additional fee information

No additional fees or cost information has been supplied for this course, please contact the provider directly.
Mathematics with Data Science at City, University of London - UCAS