Key information
- Duration:
- 4 years full time
- Typical A-level offer:
- AAB, including grade A in Mathematics.
View full entry requirements - UCAS code:
- G1G7
- Start date:
- September 2025
- 95% of our research overall in Mathematical Sciences was assessed to be world leading or internationally excellent (REF 2021)
Machine learning and data science are all around us. The need for people who can collate and interpret complex data has never been greater. This integrated Masters course will give you the skills to solve data-intensive problems. It is particularly relevant if you are interested in a research career.
You’ll explore the relationships between mathematics, data and statistics and gain a thorough grounding in theories and techniques. You’ll apply mathematical algorithms for the analysis, interpretation and visualisation of large data-sets, using real-world data.
In your mathematics modules you’ll learn the theory that forms the basis of modern data science. You’ll put this theory into practice in your data science modules. All modules are based on the latest research. Our faculty are experts in this exciting field. Their research is having significant impact in areas such as:
- artificial intelligence
- infectious disease control.
You’ll develop analytical and modelling skills, using industry-standard software such as Python and R. During your fourth year you’ll gain further skills and apply them to an advanced research project.
By graduation you’ll have necessary skills to become a capable quantitative scientist. Career options include roles in:
- the financial services
- information and digital technology
- research.
You’ll be part of a close-knit, friendly department. Our lecturers take the time to get to know you. They operate an open-door policy, so you’ll always find support if you need it.
Accreditation
- This programme is accredited to meet the educational requirements of the Chartered Mathematician designation awarded by the Institute of Mathematics and its Applications.
We understand that deciding where and what to study is a very important decision. We鈥檒l make all reasonable efforts to provide you with the courses, services and facilities described in this prospectus. However, if we need to make material changes, for example due to government or regulatory requirements, or unanticipated staff changes, we鈥檒l let you know as soon as possible.
MMath or BSc?
We also offer this course as a three-year BSc without the integrated Masters year.
Find out about Megan’s journey through her maths degree at Sussex
Course content
Find out about our types of undergraduate degrees, their structure, modules and credits
Your degree
In your first year, you’ll explore the basics of mathematics and data science.
Teaching
Teaching methods typically include:
69%: Lecture
8%: Seminar
23%: Practical
Assessment
Assessment methods typically include:
29%: Coursework
71%: Examination
Contact hours and workload
This year of study includes approximately 1,200 hours of work. This breaks down into about 264 hours of contact time and about 936 hours of independent study.
Engage and actively participate throughout your studies to get the most out of your course.
Your modules
Core modules
Core modules are taken by all students on the course. They give you a solid grounding in your chosen subject and prepare you to explore the topics that interest you most.
Autumn teaching
- Analysis 1
- Foundations of Data Analysis
- Fundamentals of Mathematics
- Linear Algebra 1
Spring teaching
- Analysis 2
- Computational Mathematics
- Data Structure and Algorithms
- Linear Algebra 2
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2025/26. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum. We’ll make sure to let you know of any material changes to modules at the earliest opportunity.
We’ll do our best to provide as much optional choice as we can, but timetabling constraints mean it may not be possible to take some module combinations. The structure of a small number of courses means that the order of modules or the streams you choose may determine whether modules are core or optional. This means that your core modules or options may differ from what’s shown here.
Check back in January 2025 for more module details.
Your degree
In Year 2, you’ll continue exploring foundations in mathematics. And you’ll add probability and statistics, computing and machine learning.
Teaching
Teaching methods typically include:
76%: Lecture
13%: Seminar
11%: Practical
Assessment
Assessment methods typically include:
38%: Coursework
62%: Examination
Contact hours and workload
This year of study includes approximately 1,200 hours of work. This breaks down into about 264 hours of contact time and about 936 hours of independent study.
Engage and actively participate throughout your studies to get the most out of your course.
Your modules
Core modules
Core modules are taken by all students on the course. They give you a solid grounding in your chosen subject and prepare you to explore the topics that interest you most.
Autumn teaching
- Calculus of Several Variables
- Introduction to Probability
- Ordinary Differential Equations
- Scientific Computing
Spring teaching
- Applied Machine Learning
- Numerical Analysis
- Probability and Statistics
- Real Analysis
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2025/26. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum. We’ll make sure to let you know of any material changes to modules at the earliest opportunity.
We’ll do our best to provide as much optional choice as we can, but timetabling constraints mean it may not be possible to take some module combinations. The structure of a small number of courses means that the order of modules or the streams you choose may determine whether modules are core or optional. This means that your core modules or options may differ from what’s shown here.
Check back in January 2025 for more module details.
Study abroad (optional)
Apply to study abroad – you’ll develop an international perspective and gain an edge when it comes to your career.
If your application to study abroad is successful, you’ll have to meet the academic requirements at Sussex and also at the partner university. Find out more about studying abroad as a Sussex student
Placement (optional)
To help you gain experience and increase your employability, you can apply for an optional placement as part of your course. You鈥檒l be responsible for applying for and securing your placement. Our dedicated careers team can provide you with information and advice. If you鈥檙e successful in obtaining a placement, this will form part of your course.
Find out more about placements and internships
Recent students have gone on placements at:
- Rolls-Royce Motor Cars Ltd
- NATS Holdings
- HEFCE.
SEPnet Employer Programme
We are a core part of the consortium, which gives us links to universities and industries across the region. SEPnet’s Employer Programme creates opportunities for our students to apply for eight-week funded summer placements.
Please note that if you鈥檙e receiving 鈥 or applying for 鈥 USA federal Direct Loan funds, you can鈥檛 transfer to the version of your course with an optional study abroad period in any country or optional placement in the USA if the number of credits for the placement/internship exceeds 25% of the total credits for your course. Find out more about American Student Loans and Federal Student Aid
Your degree
In Year 3, you’ll have the opportunity to develop your employability skills working on your project. And you can choose the topics that interest you most from a range of mathematical options.
Teaching
Teaching methods typically include:
83%: Lecture
12%: Seminar
5%: Practical
Assessment
Assessment methods typically include:
17%: Coursework
68%: Examination
1%: Practical
14%: Written assessment
Contact hours and workload
This year of study includes approximately 1,200 hours of work. This breaks down into about 264 hours of contact time and about 936 hours of independent study.
Engage and actively participate throughout your studies to get the most out of your course.
Your modules
Core modules
Core modules are taken by all students on the course. They give you a solid grounding in your chosen subject and prepare you to explore the topics that interest you most.
Autumn teaching
- Linear Statistical Models
- Partial Differential Equations
Spring teaching
- Project
- Statistical Inference
Options
Alongside your core modules, you can choose options to broaden your horizons and tailor your course to your interests. This list gives you a flavour of our options, which are kept under review and may change, for example in response to student feedback or the latest research.
While it’s our aim for students to take their preferred combinations of options, this can’t be guaranteed and will be subject to timetabling. Options may be grouped and if so, students will be able to choose a set number of options from the selection available in any particular group.
Autumn teaching
- Advanced Numerical Analysis
- Financial Mathematics
- Functional Analysis
- Introduction to Mathematical Biology
- Probability Models
Spring teaching
- Complex Analysis
- Cryptography
- Dynamical Systems
- Machine Learning and Statistics for Health
- Monte Carlo Simulations
- Numerical Solutions of Partial Differential Equations
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2025/26. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum. We’ll make sure to let you know of any material changes to modules at the earliest opportunity.
We’ll do our best to provide as much optional choice as we can, but timetabling constraints mean it may not be possible to take some module combinations. The structure of a small number of courses means that the order of modules or the streams you choose may determine whether modules are core or optional. This means that your core modules or options may differ from what’s shown here.
Check back in January 2025 for more module details.
Your degree
In your final year, you’ll focus on a research topic of your choice in your MMath project. You’ll also choose options from a range of mathematical and data science modules. This means you’ll have the opportunity to specialise in areas that interest you most, while also gaining a broad set of skills.
Teaching
Teaching methods typically include:
81%: Lecture
4%: Seminar
15%: Practical
Assessment
Assessment methods typically include:
24%: Coursework
30%: Examination
6%: Practical
40%: Written assessment
Contact hours and workload
This year of study includes approximately 1,200 hours of work. This breaks down into about 187 hours of contact time and about 1,013 hours of independent study.
Engage and actively participate throughout your studies to get the most out of your course.
Your modules
Core modules
Core modules are taken by all students on the course. They give you a solid grounding in your chosen subject and prepare you to explore the topics that interest you most.
All year
- MMath Project
Autumn teaching
- Data Science Research Methods
Spring teaching
- Machine Learning
Options
Alongside your core modules, you can choose options to broaden your horizons and tailor your course to your interests. This list gives you a flavour of our options, which are kept under review and may change, for example in response to student feedback or the latest research.
While it’s our aim for students to take their preferred combinations of options, this can’t be guaranteed and will be subject to timetabling. Options may be grouped and if so, students will be able to choose a set number of options from the selection available in any particular group.
Autumn teaching
- Advanced Numerical Analysis
- Algorithmic Data Science
- Applied Natural Language Processing
- Financial Mathematics
- Functional Analysis
- Probability Models
Spring teaching
- Advanced Natural Language Processing
- Financial Portfolio Analysis
- Image Processing
- Machine Learning and Statistics for Health
- Monte Carlo Simulations
- Numerical Solution of Partial Differential Equations
- Wider Topics in Data Science
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2025/26. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum. We’ll make sure to let you know of any material changes to modules at the earliest opportunity.
We’ll do our best to provide as much optional choice as we can, but timetabling constraints mean it may not be possible to take some module combinations. The structure of a small number of courses means that the order of modules or the streams you choose may determine whether modules are core or optional. This means that your core modules or options may differ from what’s shown here.
Check back in January 2025 for more module details.
Silver
The student experience and student outcomes are typically very high quality.
This rating was awarded in 2023, for four years.
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Find out more about our approach to teaching and supporting you to thrive
Our staff
Dr Marianna Cerasuolo
Reader in Numerical Analysis and Scientific Computation
Dr Philip Herbert
Lecturer in Numerical Analysis and Scientific Computation
A-level - contextual offer
BBB, including grade B in Mathematics.
Pearson BTEC Level 3 National Extended Certificate and two A-levels - contextual offer
Grades BB in A-levels plus Distinction in BTEC Level 3 National Extended Certificate, including grade B in Mathematics.