Undergraduate

Mathematics with Data Science

mathematics-study
DAIM building exterior
VIPER high performance computing
Katie Smith, maths student sat on wall outside library
whiteboard math calculations
The University of Hull is one of the largest providers of Data Science and AI degrees in England
Use our state of the art facilities and focus on real world data skills in our £4.5million DAIM centre
You'll have access to VIPER - our high performance super computer.
We have smaller classes than many other institutions, leading to our program being awarded 1st in the UK for academic support.
You will learn more advanced mathematics, how to work with large datasets and high performance computers as well as artificial intelligence and machine learning.
mathematics-study
DAIM building exterior
VIPER high performance computing
Katie Smith, maths student sat on wall outside library
whiteboard math calculations

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Duration

Mode

  • Standard course
  • With a foundation year

Typical offer

What does this mean?

Unlock a powerful combination of mathematical expertise and cutting-edge skills in artificial intelligence with the BSc Mathematics and Data Science degree at the University of Hull.

This programme not only equips you with a solid foundation in mathematics but also empowers you to apply these employer-sought skills to the fast-growing fields shaping the future.

Taught by experts in the field, you’ll focus on developing strong skills in computer programming and advanced mathematics, as well as how to work with large datasets, high-performance computers, artificial intelligence and machine learning.

Students with good A level results, or equivalent, may be eligible for our Gillian Stead Scholarship – worth up to £6,300 over three years.

  • Joint 1st in the UK

    for Graduate Prospects 1

  • State of the art facilities

    in our £4.5million DAIM centre

  • Access to VIPER

    our high-performance supercomputer

  • 1st in the UK

    for academic support 2

  • Be awarded £6,300

    for impressive A-level results 3

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Course overview
Module options

About this course

Skills in mathematics, data science, and artificial intelligence are pivotal competencies in driving the fourth industrial revolution and play a fundamental role in your path to career greatness.

The program is designed for students who are not only interested in the theory of mathematics but are also eager to apply that theory and develop the skills to tackle real-world challenges. Unlike traditional mathematics programs, this course places less emphasis on exams and more on authentic assessments that mirror the tasks you'll encounter in your future career, making sure you’re ready for the life of work.

In the first half of the program, you'll build a solid foundation in mathematical skills and gain proficiency in computer programming with R and Python. As you progress into the second half, you'll explore more advanced mathematical concepts, work with large datasets and high-performance computing, and delve into artificial intelligence and machine learning. Additionally, you’ll undertake a substantial final project, allowing you to deeply explore a topic of your choice and tailor your degree towards your chosen career.

The University of Hull is one of the largest providers of Data Science and AI degrees in England, equipping students with the skills to lead in tomorrow’s digital world.

Scheduled study hours and how you’re assessed

Throughout your degree, you’re expected to study for 1,200 hours per year. That’s based on 200 hours per 20 credit module. And it includes scheduled hours, time spent on placement and independent study. How this time is divided across the year varies and depends on the module you are studying.

How you'll be assessed depends on the course you study, and the modules you choose. You may be assessed through a mix of examinations, coursework, presentations and group projects.

Choose your modules

Each year, you’ll study modules worth a certain number of credits, and you need 120 credits per year. Most modules are 20 credits – so you’ll study six modules each year. Some longer modules, such as a dissertation, are worth more. In these cases, you’ll study fewer modules - but the number of credits will always add up to 120. Some modules are compulsory, some are optional, so you can build a course that’s right for you.

Preparing for Learning in Higher Education

This module is designed to give you the best possible start to your university studies, making sure you have all the essential skills you need to succeed. Through lectures and workshops we will teach you how to write in an academic style, how to find quality sources, how to reference work, culminating in writing up a mini-research project.

Compulsory•20 credits

Foundation Mathematics A

You will study pure mathematics topics, including proof, algebra, trigonometry, differentiation, integration, exponentials, logarithms, sequences and series. The applied topic is probability and statistics.

Compulsory•20 credits

Foundation Mathematics B

This module extends the knowledge gained in the Foundation Mathematics A - pure mathematics topics. You will also study functions and vectors. The applied topic is mechanics.

Compulsory•20 credits

Introduction to Physics 1

This is the first of two foundation year modules that prepare you for studying physics or mathematics at degree level. You will study the basics of mechanics, properties of matter, electricity and magnetism.

Compulsory•20 credits

Introduction to Physics 2

This is the second of two foundation year modules that prepare you for studying physics or mathematics at degree level. You will study the basics of oscillations, waves, and quantum and nuclear physics.

Compulsory•20 credits

Group Challenge (Sciences)

In a group, you'll formulate questions that can be tested by scientific investigations and take part in weekly workshops with academics.

Compulsory•20 credits
6 Modules

Introduction to programming in Python

In this module, you are introduced to the Python language, commonly used in the technology sector. As part of this course, you will learn fundamental programming concepts such as variable definition, function writing, and Boolean logic. The curriculum extends to practical skills in handling large datasets using the Pandas module and creating striking data visualisations with packages like Seaborn. These skills are then applied to numerical and Fourier analysis, essential tools for a career as a data scientist.

Compulsory•20 credits

Calculus

You'll study, for a function of a single real variable, the limit processes of differentiation and integration using logic and the language of set theory.

Compulsory•20 credits

Numbers, Sequences and Series

This module introduces the basic number systems used in mathematics and the notion of limits. You'll evaluate limits of sequences and series and determine whether they converge.

Compulsory•20 credits

Linear Algebra

This module delivers essential core mathematics. You’ll explore vectors, matrices, vector spaces, linear equation systems and dimension.

Compulsory•20 credits

Probability and Statistics

Learn how to use basic results from probability theory, such as standard probability distributions - and how to statistically estimate and test hypotheses of model parameters.

Compulsory•20 credits

Statistical Techniques in Data Science

This module introduces you to essential statistical tools used in a data science career. You will develop a strong grasp of core statistical techniques in data analysis of large multi-dimensional data sets.

Compulsory•20 credits
6 Modules

Vector Calculus

Study differentiation and integration of scalar-valued and vector-valued functions of several variables. You'll focus on applications to curves and surfaces in three-dimensional space.

Compulsory•20 credits

Differential Equations

Explore solution-generating techniques including Wronskian procedures, Laplace transforms and the method of Frobenius, concluding with the more advanced application of Sturm-Liouville theory.

Compulsory•20 credits

Introduction to Machine Learning

In the module you will be introduced to the concept of machine learning and explore why machines need the ability to learn. You will learn the mathematical techniques and methods used in the field of machine learning, and develop practical computational skills that are required to apply these techniques to real-world problems. You will learn how to create and interpret clear visualisations of the results of machine learning.

Compulsory•20 credits

Big Data & High-Performance Computing

This module shows you a range of practical applications of data science by examining closely how we mine data from big data sets. This covers a range of approaches from SQL and databases to association pattern mining and is underpinned by an ethical framework. We will also teach you how to use the powerful high-performance computers, which can enable you to use even larger datasets.

Compulsory•20 credits

Functions of a Complex Variable

On this module, you'll study differentiation and integration of a complex-valued function of a complex-valued variable. 

Optional•20 credits

Statistical Models

This module investigates nonparametrical tests, such as goodness-of fit and rank tests. You’ll also learn how to use linear regression models and analysis of variance.

Optional•20 credits

Partial Differential Equations

Study methods for solving first- and second-order partial differential equations, mainly for scalar-valued functions of two or more variables.

Optional•20 credits
7 Modules

Mathematical Project

Under the supervision of your supervisor, you will perform an in-depth examination of a mathematical topic of your choice. There is also the option to undertake an education project with a placement for those interested in pursuing teaching as a career.

Core•40 credits

STEM Education Projects

On this module you will gain valuable experience in the professional environment of education via placements at local schools, colleges or other educational organisations. You will be a role model for science in the classroom and at the same time train your communication and collaborative skills. You will also develop and deliver an Educational Activity as part of your placement on a topic of your choice.

This module will give you valuable teaching experience if you decide to go into postgraduate teacher training, but also if you plan to work in the conservation sector, educating the public in their perception of the natural world.

Core•40 credits

Advanced Machine Learning and Neural Networks

This module will develop an in-depth understanding of advanced methods in machine learning and neural networks. The module will teach cutting edge deep learning models at the forefront of this field, along with the computational skills needed to apply these models to tackle common problems encountered in the real world.

Compulsory•20 credits

AI-Assisted Modelling of Complex Systems

This module connects machine learning to mechanistic modelling within the context of systems theory, especially biological systems. What is a system and what makes a system complex? Why are differential equations appropriate for modelling large populations of cells? Why do agent-based models describe small populations better? How are molecular species connected in a cell? How do systems biologists model these networks? In addition to finding out the answers, the student will use genetic algorithms to schedule chemotherapy, supervised learning to streamline numerical simulations, unsupervised learning to interpret simulation results, and the Apriori algorithm to select kinetic parameters.

Compulsory•20 credits

Differential Geometry

Study curves and surfaces in 3D using vector calculus, linear algebra and analysis. How do you make a map of the world? What is the Möbius strip? How curved is a sphere or a cube?

Optional•20 credits

Advanced Numerical Computation

As soon as you look beyond a textbook, you will quickly see that most mathematical problems in fields such as quantum mechanics, fluids dynamics and epidemiology involve complex differential equations that are too difficult to solve without using a computer. In this module, you'll learn via hands on programming how to solve these problems numerically.

Optional•20 credits

Classical and Quantum Mechanics

Explore the strange quantum world where the behaviour of subatomic particles is described by integrals, complex numbers, and the rules of probability.

Optional•20 credits

Mathematical Biology

Mathematical models can be applied to a wide range of applications in biology. Without assuming any prior biological knowledge, this module describes how mathematics can be used to understand topics that are encountered in biological applications such as population dynamics for a single population, interacting populations and law of mass action. This module emphasises model construction and development.

Optional•20 credits

Computational Applied Statistics

In this age of big data, the ability to analyse large datasets and extract useful information from them becomes increasingly important. This module focuses on several machine learning techniques that can be used for this. You will also learn how to use Python/R for data science applications.

Optional•20 credits

In third year, you will either undertake the Mathematical Project OR the STEM Education Project, as well as the two other compulsory modules, and two optional modules.
9 Modules

Playlist

Dr Daniel Farrow

Course Overview 2 mins

Katie Smith

Student story 1 min

Teaching facilities

University Life 1 min

Accommodation at Hull

University Life 2 mins

Entry requirements

What do I need?

When it comes to applying to university, you'll need a certain number of UCAS points. Different qualifications and grades are worth a different amount of points. For this course, you'll need…

Use UCAS's calculator to work out your estimated points

We consider experience and qualifications from the UK and worldwide which may not exactly match the combinations above.

But it's not just about the grades - we'll look at your whole application. We want to know what makes you tick, and about your previous experience, so make sure that you complete your personal statement.

Have questions? Our admissions team will be happy to help.

What do I need?

If you require a student visa to study or if your first language is not English you will be required to provide acceptable evidence of your English language proficiency level.

See other English language proficiency qualifications accepted by the University of Hull.

If your English currently does not reach the University’s required standard for this programme, you may be interested in one of our English language courses.

Visit your country page to find out more about our entry requirements.

Fees & funding

How much is it?

Additional costs you may have to pay

Your tuition fees will cover most costs associated with your programme. There are some extra costs that you might have to pay, or choose to pay, depending on your programme of study and the decisions you make:

  • Books (you can borrow books on your reading lists from the library, but you may buy your own)
  • Optional field trips
  • Study abroad (incl. travel costs, accommodation, visas, immunisation)
  • Placement costs (incl. travel costs and accommodation)
  • Student visas (international students)
  • Laptop (you’ll have access to laptops and computers on campus, but you may want your own)
  • Printing and photocopying
  • Professional-body membership
  • Graduation (gown hire and photography)

Remember, you’ll still need to take into account your living costs. This could include accommodation, travel, food and more.

How do I pay for it?

How much is it?

Additional costs you may have to pay

Your tuition fees will cover most costs associated with your programme. There are some extra costs that you might have to pay, or choose to pay, depending on your programme of study and the decisions you make:

  • Books (you can borrow books on your reading lists from the library, but you may buy your own)
  • Optional field trips
  • Study abroad (incl. travel costs, accommodation, visas, immunisation)
  • Placement costs (incl. travel costs and accommodation)
  • Student visas (international students)
  • Laptop (you’ll have access to laptops and computers on campus, but you may want your own)
  • Printing and photocopying
  • Professional-body membership
  • Graduation (gown hire and photography)

Remember, you’ll still need to take into account your living costs. This could include accommodation, travel, food and more.

How do I pay for it?

Our academics

Our staff cover a wide range of expertise including but not limited to, mathematics sciences, modelling, physics, astronomy, computer science, criminology, engineering, health and healthcare, and the geosciences. With access to state-of-the-art computation facilities in the new DAIM building and double monitors for enhanced data visualisation, you will be trained on the most modern computations facilities possible. 

See more academics for this subject
Dr Jie Yang
Featured academic

Dr Jie Yang

Jie joined the University of Hull in 2021 as a Lecturer in Applied Mathematics. She has a PhD in Systems Biology and her principal research interests involve the use of applied mathematics for biological applications.
Dr Daniel Farrow
Featured academic

Dr Daniel Farrow

Daniel Farrow has over 50 co-authored publications with almost 4700 citations combined. He is Director of Education in the Centre of Excellence for Data Science, AI and Modelling (DAIM).

Take a look at our facilities

DAIM

You’ll find 250 of the highest-spec PCs in this new, state-of-the-art facility where you’ll learn, practice and apply your coding, programming, AI and data science skills.

Superlab

Fully refurbished as part of a significant investment in high-performance workstations, servers and social spaces, our Superlab is also open to students outside of teaching hours.

Python

All of our students have access to powerful industry-standard software such as Python to develop your skills and prepare for your future career.

Supercomputing

You’ll have access to Viper – the highest-spec computer at any university in the North of England.

See more in our virtual tour
DAIM building exterior
students in the SuperLab Computer Suite
one of the computers in the Turing Lab
VIPER high performance computing
DAIM building exterior
students in the SuperLab Computer Suite
one of the computers in the Turing Lab
VIPER high performance computing
numbers

Future prospects

Our career-focused mathematics with data science degree will help you gain skills that are in high demand with employers and open doors to a career in mathematics, data science, civil service, banking and finance, numerical computing, teaching and more. 

At the end of the BSc, you could transfer onto one of our one-year taught mathematics or data science masters, which lets you access careers that require a postgraduate degree.

University of Hull Open Day

Your next steps

Like what you’ve seen? Then it’s time to apply.

The standard way to apply for this course is through UCAS. This will give you the chance to showcase your skill, qualities and passion for the subject, as well as providing your academic qualifications.

How to apply

Not ready to apply?

Visit our next Open Day, and see all that Hull has to offer for yourself. Talk to our lecturers about your subject, find out what university is really like from our current students, and take a tour of our beautiful campus and amazing facilities.

Book your place now

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[1] (Mathematics) Complete University Guide 2025

[2] (Mathematics) National Student Survey 2024

[3] 128 UCAS points (including 48 points in Maths) qualifies you for the Gillian Stead Bursary: £2,100 for first year students from the UK or the EU. Subject to results, you'll get a further £2,100 in each year of your degree.

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