Mathematics with Machine Learning BSc (Hons)
Learn to build machine learning models, and understand the mathematics and algorithms that underpin them. Study theories used in AI, neural networks and Python coding
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Overview
Understand the mathematics that underpins artificial intelligence, and develop the skills needed to build machine learning models.
You鈥檒l make yourself vital to an age of artificial intelligence by building invaluable theoretical and practical abilities. You鈥檒l study powerful mathematical concepts and tools, and bring them to bear on subjects like machine learning, neural networks, and Python coding.
Once you graduate, you鈥檒l be set to enter any of the industries being transformed by AI and machine learning tools. You'll learn how to apply large language models such as ChatGPT, and how to analyse images and other live data coming from sectors such as healthcare, education and business. You'll also be ready to move into roles that rely on mathematical understanding, such as finance or government, or to take up postgraduate study in maths or artificial intelligence.
Course highlights
- Develop a rounded understanding of modern mathematics, including calculus, linear algebra and probability, with a focus on machine learning tools, theories and methods
- Apply your learning with modules in programming languages such as Python, Mathematica and R
- Learn how to use industry standard tools for building machine learning models such as scikit-learn, PyTorch and TensorFlow
- Study alongside world-class researchers in machine learning and mathematics, in a department placed in the top ten for teaching in the 2022 NSS report
- Build your career prospects with built-in employability programmes, placement support and careers advice
- Brush up your skills with our drop-in Maths Cafe and personal tutorial system
Top 30
for student satisfaction
(Times Higher Education, 2024)
Maths at 1024核工厂 鈥 number 8 in the UK for student satisfaction, and the top modern university in the country for research quality
National Student Survey (NSS) 2023 and Research Excellence Framework (REF) 2021
Contact information
Contact AdmissionsClearing is open
This course is available through Clearing.
How to apply for accommodation
We have a variety of accommodation options, including studios, en-suites, catered, self-catered and private rental options. See how our housing team can help you find a place to call home.
Clearing FAQs
To work out your UCAS points, use our UCAS Calculator to work out how many UCAS points you have.
The tariff calculator will allow you to see what grades you need to get into your preferred course at 1024核工厂.
You can apply through Clearing if:
- You don't meet the conditions of your offer for your firm (first) or insurance (second) choice courses
- Your exam results are better than you expected and you want to change your course or university
- You don't hold any offers
- You've accepted an offer but changed your mind about the course you want to do
- You're applying for the first time after 30 June 2024
After we make you an offer we'll send you a confirmation email. This email will let you know what you need to do next and it will tell you what you need to provide us. In some instances we may ask you to send us copies of certificates or you may need to send us a portfolio.
If you've previously applied through UCAS you'll need to use your UCAS Hub to accept our offer by adding us as your Clearing choice.
If you're having issues, please contact us on +44 (0)23 9284 8090 or admissions@port.ac.uk
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See our accommodation page for more information.
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See more on visa advice.
If you would like further information or guidance, please contact our international office or call our International Clearing Hotline on +44(0)23 9284 8785.
Entry requirements
BSc (Hons) Mathematics and Machine Learning entry requirements
Typical offers
- UCAS points - 112-120 points from 2 or 3 A levels, or equivalent, including 40 points from Mathematics. (calculate your UCAS points)
- A levels - BBB-BBC
- International Baccalaureate - 29
You may need to have studied specific subjects or GCSEs 鈥 .
English language requirements
- English language proficiency at a minimum of IELTS band 6.0 with no component score below 5.5.
We also accept other standard English tests and qualifications, as long as they meet the minimum requirements of your course.
If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.
We look at more than just your grades
While we consider your grades when making an offer, we also carefully look at your circumstances and other factors to assess your potential. These include whether you live and work in the region and your personal and family circumstances which we assess using established data.
If you don't meet the entry requirements, you may be able to join this course after you successfully complete a foundation year.
Facilities and specialist software
Maths Caf茅
No problem is too small or too tough for our Maths Caf茅 tutors, who are on hand every day during term-time to help you if you get stuck or need something explained.
Future Technology Centre, Technology Enhanced Active Learning Space
Develop teamwork and communication skills to prepare you for your graduate job and make yourself more employable, while getting to know your classmates in an informal and friendly environment.
Computer labs and specialist mathematics software
Learn several specialist programming, symbolic and data handling languages such as Python, Mathematica and R 鈥 and work with industry standard tools for building machine learning models, such as scikit-learn, pytorch and tensorflow.
Careers and opportunities
Studying machine learning shows you鈥檙e committed to understanding the needs of the growing artificial intelligence sector. Forbes magazine predicts a , and research suggests that .
You鈥檒l also graduate with a deep understanding of the mathematical principles, theories and methods that make machine learning possible - unlike other degrees in this field, our degree in Mathematics and Machine Learning is designed to give you the underlying understanding that will help you grasp future developments in the sector.
Additionally, your mathematical study will make you employable in sectors beyond machine learning, as you鈥檒l be able to show your readiness for careers in finance, analysis, or anywhere that analytical problem-solving is a bonus.
Typical roles
You can expect to apply for roles like 鈥渕achine learning engineer鈥 or 鈥渕achine learning scientist鈥; or, more broadly, titles like 鈥渄ata engineer鈥 or 鈥渄ata scientist鈥. More generally, you鈥檒l find your ability to build models that learn from data is in demand in sectors such as finance, education, retail, defence, government research.
Ongoing career support 鈥 up to 5 years after you graduate
Get experience while you study, with support to find part-time jobs, volunteering opportunities, and work experience.
Towards the end of your degree and for up to five years after graduation, you鈥檒l receive one-to-one support from our Graduate Recruitment Consultancy to help you find your perfect role.
Modules
What you'll study
Core modules
Analyzing function behavior through limits, derivatives and integrals, you'll use differential calculus, integral calculus for area computations, determine series convergence, and apply infinite series to differentiation/integration.
You'll develop career-building skills in applying these modern software packages to current mathematical problems, learning to implement algorithms, break problems into coded steps, visualise data, and further skills needed by companies employing mathematics and physics graduates.
You'll solve problems and prove theorems using matrices, vectors, linear transformations, vector spaces and detailed eigen theory.
You'll develop proof techniques through examples, discussing when different proof types are useful. As you hone your ability to speak in logic, the 'language' used to prove mathematical statements, you'll also work with mathematical concepts like sets, functions, ciphers and complex numbers.
You'll learn to formulate problems algebraically, create graphical solutions to linear problems, and interpret ordinary differential equations (ODEs). You'll also demonstrate that some problems are too complicated for these methods, and create approximate solutions using numeric techniques.
You'll apply statistical theory and data analysis techniques used in business, testing hypotheses and performing regression modelling with Minitab software.
Core modules
You'll model an issue drawn from live, open-ended problems, identify and implement practical methods to analyse and solve your chosen problem, then produce reports to communicate your analysis professionally. You'll also work with careers guidance to relate your skills and interests to opportunities, and recognise how to best present yourself in effective applications and interviews.
Determining vector calculus gradients, divergences and curls, you will evaluate line, surface and volume integrals, apply integral theorems, find Fourier series, solve differential equations analytically and interpret solutions.
In this module, you'll study the methods used to build supervised and unsupervised machine learning models. Combining traditional pen-and-paper mathematics with powerful computational methods, you'll train machine learning models to fit parameters, learn patterns, and make predictions.
Optional modules
You'll formulate and solve linear and non-linear programming models, applying your skills to operational research problems, and prepare for advanced modelling studies in simulation, forecasting and other forms of planning.
You'll look at sequences and series, construct proofs and counter-examples, and look at the differentiation and integration of real and complex functions. You'll emerge from this module able to define and apply theorems, illustrate complex mappings, understand properties of standard complex functions, and use techniques like evaluating derivatives/integrals to solve problems.
You'll construct group theory proofs and show counterexamples. explore modular arithmetic and Euclidean division, and build your toolkit for your final year studies in modern algebra.
You'll apply creative mathematical and programming methods to model and analyse financial problems. Through simulations of finance scenarios, you'll examine and address practical questions in advanced market dynamics.
First, you'll master analytical mechanics using Lagrangian and Hamiltonian techniques, reducing complex systems into simpler, symmetric forms. Then you'll analyse chaotic dynamics with differential and difference equations. When you complete the module, you'll have developed lasting intuition and problem-solving agility, with a versatile toolkit of theory and techniques essential for any physics career.
In this module, you'll learn to formulate and communicate problems in statistical terms, study estimation and sampling, and interpret the results of advanced models and experiments.
You'll investigate planetary motion, stars and galaxies through concepts including celestial coordinates, physical laws and gravity. As you model stellar properties and evolution, from atmospheres to remnants like black holes, you'll bring your analysis alive through interactive software, topical news and observing sessions.
Core modules
You'll study theories and practices for advanced machine learning in this module, including neural networks, deep learning and generative models. Covering supervised and unsupervised forms of machine learning, you'll work with commercial software like PyTorch, and learn the underlying mathematical principles as you do. You'll emerge from the module ready to engage with complex industry data, using efficient computational models.
Using freely available modern datasets, you'll learn to select and apply appropriate statistical techniques, using methods such as principal components and clustering. You'll also demonstrate your ability to apply statistical learning techniques in programming languages like R or Python.
Optional modules
Adapting to the school environment, you'll explore STEM themes with classes from Key Stage 3 to Sixth Form, before reflecting critically on teaching practices.
Through this mentorship of mathematics and physics teachers, you'll get direct experience of STEM education, break down stereotypes of mathematics, and prove your ability to communicate difficult concepts.
You'll study multiple types of options to understand their payoffs, and how to construct portfolios with different investment strategies. You'll also derive the famous Black-Scholes equation for pricing options in different contexts, explore exotic options, and calculate risk exposure in a hedging process.
In this module, you'll analyse 4-dimensional spacetime from Special Relativity, gaining skills in tensor algebra and calculus. You'll derive and apply Einstein's equations yourself, modeling black holes or gravitational waves, as you develop your skills in independent thinking, curiosity, and clear communication.
As you work through key concepts, such as nuclear processes, relativity and cosmology, you'll evaluate observational issues like the quest for dark matter. On completion, you'll have the critical thinking and intellectual curiosity to solve real problems modelling cosmic structures.
In this module, you'll use perturbation theory and relevant software, such as MATLAB, to examine equilibria, bifurcation and integrability. You'll build on your understanding from previous modules, such as calculus and computational management, and learn to apply them to problems that exceed the limits of linear systems theory.
You'll study heat, wave and Laplace equations, with applications in science.
Gaining solid knowledge for a career in supply chain management or further study, you'll synthesize new and existing ideas to generate creative solutions to supply chain problems.
Learning about strengths and weaknesses of population sampling and study designs, you will be introduced to appropriate statistical analysis tools including multivariate techniques and modeling data in SPSS. You'll formulate common epidemiological statistics, construct life tables, design clinical trials, and employ multivariate methods, all using tools designed for applied statisticians in health research.
You'll plan your project, gather and synthesize literature, and write a dissertation to present your independent discoveries. You'll then evaluate your own work, and learn to present and discuss your conclusions in writing and through oral presentations.
Through industry case studies, you'll formulate and implement linear, integer programming models for planning and risk analysis. Using industry-standard software, you'll evaluate solutions and communicate data-driven insights tailored for stakeholders. When you complete the module, you'll be able to demonstrate versatile skills in synthesising information, assessing trade-offs and driving impact through evidence-based advice.
After your second or third year, you can do an optional study abroad or work placement year to get valuable longer-term work experience in the industry.
We鈥檒l help you secure a work placement that fits your aspirations. You鈥檒l get mentoring and support throughout the year.
Changes to course content
We use the best and most current research and professional practice alongside feedback from our students to make sure course content is relevant to your future career or further studies.
Therefore, some course content may change over time to reflect changes in the discipline or industry. If a module doesn't run, we'll let you know as soon as possible and help you choose an alternative module.
Study Mathematics at the 1024核工厂
Meet your staff, facilities and equipment
Get an introduction to mathematics at 1024核工厂 from Professor Daniel Thomas, Head of the School of Mathematics and Physics, and colleagues. Explore our facilities and equipment, and discover more about your prospects as a maths graduate.
Daniel Thomas: What excites me most about university education is that it is right at the interface between research and teaching. Newly acquired skills and knowledge get passed on to the next generation directly, to you.
The 1024核工厂 is providing mathematics staff and students just with the right space in the right environment to do exactly that.
Our research, as well as our teaching, are concentrated in this building in the Lion Gate Building.
We will now move on to our lecture theatre where Dr. Marianna Cerasuolo will tell us more about the facilities we have in this building.
Marianna Cerasuolo: In the first year, all of our students take compulsory modules in core subjects which are necessary to become very good mathematicians. In the second and third year, they have a wide variety of options they can choose.
In particular, they can decide either to stay on straight mathematics, so what we call the BSc Mathematics, or to take different, more specialised paths. For example, mathematics for finance and management or mathematics with statistics.
We have also other types of options like astrophysics or cosmology and general relativity, or they can decide to do operational research and logistics. Actually, we have a very strong research group who works on this particular subject.
So since the first year, our students learn that mathematics in its entirety has lots of real life applications. They also learn to work together as a team, and that makes them very valuable for companies once they finish their degree with us.
Daniel Thomas: The nice thing about our school is that the staff offices are right next to the lecture theatre and the computer lab. We have an open door policy because we want to support your learning the best we can. You can pop in our staff office any time during the day and ask our staff about the lectures or about the course material, any questions about mathematics that you may have.
We will now move on to our computer lab where Dr. James Burridge, reader in statistical physics, will tell you about the facilities we have.
James Burridge: In my research, I use tools of probability, physics, and machine learning to build models of language, and to understand what we can learn about people from the way they speak. My models use many different kinds of data, including detailed geographical information, large scale linguistic surveys and audio.
Using big data to model the real world, identifying patterns and making predictions are commercially valuable skills. Some people say they are driving a fourth industrial revolution. Here at 1024核工厂, we will teach you the mathematics of modelling and prediction, which can be applied to problems in biology, health care and a whole range of commercial applications.
Using computer labs like this one, we will teach you state of the art machine learning techniques to solve real world problems. These can include recognising emotions from speech data, predicting and classifying images and modelling behaviour.
Daniel Thomas: The Technology Learning Centre at the ground floor of Lion Gate Building is a perfect space for students to study, to learn, to meet or just to hang out. We also use the space to offer our daily tutorials, the maths cafe, where our mathematics staff are providing tutorials to our mathematics students, where you can ask any questions about mathematics.
We look forward to welcoming you at the 1024核工厂 to discover the beauty of mathematics with us.
Teaching
On this course, you'll be taught in:
- Lectures, including active participation in which you'll try out the material being taught in the lecture
- Tutorials and special exercise classes to practise your learning
- Online teaching videos and resources
- Independent study
You can access all teaching resources on Moodle, our virtual learning environment, from anywhere with a web connection.
How you're assessed
You'll be assessed through written and practical exams, coursework and in-class tests. While most modules have an exam element, no module is wholly based on a single exam result.
You鈥檒l be able to test your skills and knowledge informally before you do assessments that count towards your final mark, and use feedback from your practice and formal assessments so you can improve in the future.
How you'll spend your time
One of the main differences between school or college and university is how much control you have over your learning.
We use a blended learning approach to teaching, which means you鈥檒l take part in both face-to-face and online activities during your studies. As well as attending your timetabled classes you'll study independently in your free time, supported by staff and our virtual learning environment, Moodle.
A typical week
We recommend you spend at least 35 hours a week studying for your Mathematics with Machine Learning degree. You鈥檒l be in timetabled teaching activities such as lectures, practical classes and workshops for about 19 hours a week. The rest of the time you鈥檒l do independent study such as research, reading, coursework and project work, alone or in a group with others from your course. You'll probably do more independent study and have less scheduled teaching in years 2 and 3, but this depends on which modules you choose.
Most timetabled teaching takes place during the day, Monday to Friday. Optional field trips may involve evening and weekend teaching or events. There鈥檚 usually no teaching on Wednesday afternoons.
Term dates
The academic year runs from September to June. There are breaks at Christmas and Easter.
Supporting you
You'll get about 18 hours per week face-to-face contact time, plus support via video, phone and face-to-face from teaching and support staff to enhance your learning experience and help you succeed. You can build your personalised network of support from the following people and services:
Types of support
Your personal tutor helps you make the transition to independent study and gives you academic and personal support throughout your time at university.
As well as regular scheduled meetings with your personal tutor, they're also available at set times during the week if you want to chat with them about anything that can't wait until your next meeting.
You'll have help from a team of faculty learning support tutors. They can help you improve and develop your academic skills and support you in any area of your study in one-on-one and group sessions.
They can help you:
- master the mathematics skills you need to excel on your course
- understand engineering principles and how to apply them in any engineering discipline
- solve computing problems relevant to your course
- develop your knowledge of computer programming concepts and methods relevant to your course
- understand and use assignment feedback
All our labs and practical spaces are staffed by qualified laboratory support staff. They鈥檒l support you in scheduled lab sessions and can give you one-to-one help when you do practical research projects.
During term time, Faculty Academic Skills Tutors (AST) are available for bookable 1-to-1 sessions, small group sessions and online sessions. These sessions are tailored to your needs.
Support is available for skills including:
- University study
- Getting into the right study mindset
- Note-taking and note-making skills
- Referencing
- Presentation skills
- Time management, planning, and goal setting
- Critical thinking
- Avoiding plagiarism
If you have a disability or need extra support, the Additional Support and Disability Centre (ASDAC) will give you help, support and advice.
Our online will help you plan for managing the challenges of learning and student life, so you can fulfil your potential and have a great student experience.
You can get personal, emotional and mental health support from our Student Wellbeing Service, in person and online. This includes 1鈥2鈥1 support as well as courses and workshops that help you better manage stress, anxiety or depression.
If you require extra support because of a disability or additional learning need our specialist team can help you.
They'll help you to
- discuss and agree on reasonable adjustments
- liaise with other University services and facilities, such as the library
- access specialist study skills and strategies tutors, and assistive technology tutors, on a 1-to-1 basis or in groups
- liaise with external services
Library staff are available in person or by email, phone, or online chat to help you make the most of the University鈥檚 library resources. You can also request one-to-one appointments and get support from a librarian who specialises in your subject area.
The library is open 24 hours a day, every day, in term time.
The Maths Cafe offers advice and assistance with mathematical skills in a friendly, informal environment. You can come to our daily drop-in sessions, develop your mathematics skills at a workshop or use our online resources.
If English isn't your first language, you can do one of our English language courses to improve your written and spoken English language skills before starting your degree. Once you're here, you can take part in our free In-Sessional English (ISE) programme to improve your English further.
Costs and funding
Tuition fees
- UK/Channel Islands and Isle of Man students 鈥 拢9,535 per year (may be subject to annual increase)
- EU students 鈥 拢9,535 a year (including Transition Scholarship 鈥 may be subject to annual increase)
- International students 鈥 拢17,900 per year (subject to annual increase)
Funding your studies
Find out how to fund your studies, including the scholarships and bursaries you could get. You can also find more about tuition fees and living costs, including what your tuition fees cover.
Applying from outside the UK? Find out about funding options for international students.
Additional costs
Our accommodation section show your accommodation options and highlight how much it costs to live in 1024核工厂.
You鈥檒l study up to 6 modules a year. You may have to read several recommended books or textbooks for each module.
You can borrow most of these from the Library. If you buy these, they may cost up to 拢60 each.
We recommend that you budget 拢75 a year for photocopying, memory sticks, DVDs and CDs, printing charges, binding and specialist printing.
If your final year includes a major project, there could be cost for transport or accommodation related to your research activities. The amount will depend on the project you choose.
If you take a placement year or study abroad year, tuition fees for that year are as follows:
- UK/Channel Islands and Isle of Man students 鈥 拢1,385 a year (may be subject to annual increase)
- EU students 鈥 拢1,385 a year, including Transition Scholarship (may be subject to annual increase)
- International students 鈥 拢2,875 a year (subject to annual increase)
Apply
Ready to apply?
To start this course in 2025, apply through UCAS. You'll need:
- the UCAS course code 鈥 G500
- our institution code 鈥 P80
If you'd prefer to apply directly, use our online
You can also sign up to an Open Day to:
- Tour our campus, facilities and halls of residence
- Speak with lecturers and chat with our students
- Get information about where to live, how to fund your studies and which clubs and societies to join
If you're new to the application process, read our guide on applying for an undergraduate course.
Applying from outside the UK
As an international student you'll apply using the same process as UK students, but you鈥檒l need to consider a few extra things.
You can get an agent to help with your application. Check your country page for details of agents in your region.
Find out what additional information you need in our international students section.
If you don't meet the English language requirements for this course yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.
Admissions terms and conditions
When you accept an offer to study at the 1024核工厂, you also agree to abide by our Student Contract (which includes the University's relevant policies, rules and regulations). You should read and consider these before you apply.