Undergraduate Course

Integrated Master in Science: Mathematics and Data Science

Now In Clearing

Overview

The details

Course: Mathematics and Data Science

UCAS code: G199

Start date: October 2021

Study mode: Full-time

Maximum duration: 4 years

Location: Colchester Campus

Based in: Mathematical Sciences

Data is the lifeblood of our society and mathematics is the language that underpins the science of understanding that data. From medicine to government offices, and market research to the environment, the collection and analysis of data is crucial to understanding how to improve, create and guide products and services across the globe. The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

Our MSci Mathematics and Data Science is an Integrated Masters course that will cover key skills in mathematics and data science giving you the opportunity to apply theory and methods to real-world problems. You’ll foster your understanding of mathematics, develop skills to use smart devices efficiently and use statistical techniques and methods to interpret and exploit big data.

The concept and skill of a programming language are the crucial basis for skills in data base programming and management, in developing data processing pipelines and in organising and analysing large and massive data sets. This course will introduce you to programming language Python and R for statistical analysis and data visualisation. In your third year and fourth year, analysing data and methods in group projects will be essential capstone modules for the learning outcomes of the course.

Topics include:

Mathematical skills including, applied mathematics, pure mathematics and optimisation
Computer science and programming
Statistics and operations research
Artificial intelligence, databases and information retrieval
Ethical issues around the use and processing of data
Specialist skills in the areas of big data, data analytics and data science

Our Integrated Masters gives you the opportunity to fast track your degree and complete your final year in nine months compared to a regular MSc which usually takes twelve months. Combining your undergraduate and postgraduate study in one degree will give you a strong theoretical background as well as specialist expertise through independent research. This combination makes graduates from our course attractive candidates for many employers.

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines. You therefore can gain an exceptional range of knowledge and skills that are currently in demand in mathematically oriented employment; in business, commerce, industry, government service, education and in the wider economy.

Why we're great.

You have access to our ultramodern facilities at our new STEM Centre that provide real-world experience.
You join a community of scholars leading the way in technological research and development.
An incredible 89% of our undergraduate maths students are in employment or further study (Graduate Outcomes 2020).

THE Awards 2018 - Winner University of the Year

Our expert staff

We are also home to many of the world’s top scientists, and our staff are driven by creativity and imagination as well as technical excellence. We conduct world-leading research in areas such as explorative data analysis, classification and clustering, evolutionary computation, data visualisation and financial forecasting. As well as being world-class academics, our staff are award-winning teachers. Many of our academics have won national or regional awards for lecturing, and many of them are qualified and accredited teachers – something which is very rare at a university.

We are a small but influential department, so our students and staff know each other personally. You never need an appointment to see your lecturers and professors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

Specialist facilities

In addition to teaching, we have a Maths Support Centre, which offers help to students on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
We have a dedicated social and study space for Maths students in the department, which is situated in the new £18m STEM Centre
We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

Demand for skilled graduates in the areas of mathematics, big data and data science is growing rapidly in both the public and private sector, and there is a predicted shortage of data scientists with the skills to understand and make commercial decisions based on the analysis of big data. An incredible 89% of our undergraduate maths students are in employment or further study (Graduate Outcomes 2020).

A successful career in data science requires you to possess truly interdisciplinary knowledge, so we’ll ensure you graduate with a wide-ranging yet specialised set of skills in this area. You are taught mainly within our Department of Mathematical Sciences and our School of Computer Science and Electronic Engineering, but also benefit from input from our Essex Business School, and our Essex Pathways Department. Mathematicians and data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course can open the door to almost any industry, from health, to government, to publishing.

The University of Essex is bridging the gap between academia and business, and we are at the forefront of helping the UK grasp the big data opportunities to get ahead in the global race. Our graduates in data science have been very successful in finding employment in the public sector, consulting, technology, retail, and utilities, while a number have gone on to postgraduate study or research.

We have a large pool of external contacts, ranging from companies providing robots for the media industry, through vehicle diagnostics, to the transforming of unstructured data to cloud-based multidimensional data cubes, who work with us and our students to provide advice, placements and eventually graduate opportunities.

We also work with our University's Student Development Team to help you find out about further work experience, internships, placements, and voluntary opportunities.

Entry requirements

Clearing entry requirements

Specific entry requirements for this course in Clearing are not published here but for most of our degree courses you will need to hold a Level 3 qualification. If you are interested in applying and have already received your results, use our Clearing application form to apply for 2021 entry and find out if you are eligible. You will be asked to provide details of your qualifications and grades.

Structure

Course structure

We offer a flexible course structure with a mixture of compulsory and optional modules chosen from lists. The first three undergraduate years listed below are an example structure from the current academic year. Your course structure could differ from this if modules change from year-to-year. The final Masters year shows you all of the modules currently available (compulsory and optional) so you can see the breadth of what is on offer.

Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The course content is therefore reviewed on an annual basis to ensure our courses remain up-to-date so modules listed are subject to change.

Teaching and learning disclaimer

Following the impact of the pandemic, we made changes to our teaching and assessment to ensure our current students could continue with their studies uninterrupted and safely. These changes included courses being taught through blended delivery, normally including some face-to-face teaching, online provision, or a combination of both across the year.

The teaching and assessment methods listed show what is currently planned for 2021 entry; changes may be necessary if, by the beginning of this course, we need to adapt the way we’re delivering them due to the external environment, and to allow you to continue to receive the best education possible safely and seamlessly.

Components and modules explained

Components

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

Status	What this means
Core	You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options	You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory	You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Compulsory with Options	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Optional	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code. For example, the module code HR100-4-FY means:

100

The department or school the module will be taught by.

In this example, the module would be taught by the Department of History.

The module number.

The UK academic level of the module.

A standard undergraduate course will comprise of level 4, 5 and 6 modules - increasing as you progress through the course.

A standard postgraduate taught course will comprise of level 7 modules.

A postgraduate research degree is a level 8 qualification.

The term the module will be taught in.

AU: Autumn term
SP: Spring term
SU: Summer term
FY: Full year
AP: Autumn and Spring terms
PS: Spring and Summer terms
AS: Autumn and Summer terms

COMPONENT 01: CORE

Calculus

(30 CREDITS)

This module will allow you to build your knowledge of differentiation and integration, how you can solve first and second order differential equations, Taylor Series and more.

View Calculus on our Module Directory

COMPONENT 02: CORE

Matrices and Complex Numbers

(15 CREDITS)

Can you perform simple operations on complex numbers? How do you solve systems of linear equations using row operations? Can you calculate the determinant and inverse of a matrix? Understand the basics of linear algebra, with an emphasis on vectors and matrices.

View Matrices and Complex Numbers on our Module Directory

COMPONENT 03: CORE

Statistics I

(15 CREDITS)

How do you apply the addition rule of probability? Or construct appropriate diagrams to illustrate data sets? Learn the basics of probability (combinatorial analysis and axioms of probability), conditional probability and independence, and probability distributions. Understand how to handle data using descriptive statistics and gain experience of R software.

View Statistics I on our Module Directory

COMPONENT 04: COMPULSORY

Discrete Mathematics

(15 CREDITS)

This module will provide you with a foundation of knowledge on the mathematics of sets and relations. You will develop an appreciation of mathematical proof techniques, including proof by induction.

View Discrete Mathematics on our Module Directory

COMPONENT 05: COMPULSORY

Mathematical and Computational Modelling

(15 CREDITS)

This module introduces you to programming skills in the context of a range of mathematical modelling topics. Mathematical modelling skills will be an important focus alongside learning how to structure and implement codes in both Matlab and R. A key part of the module will be investigative open-ended computational modelling studies at both the group and individual level.

View Mathematical and Computational Modelling on our Module Directory

COMPONENT 06: COMPULSORY

Mathematical Skills

(15 CREDITS)

Want to develop your mathematical skills by solving problems that are varied in nature and difficulty? Keen to write mathematical arguments that explain why your calculations are answer a question? Examine problem-solving techniques for situations across mathematics, including calculus, algebra, combinatorics, geometry and mechanics.

View Mathematical Skills on our Module Directory

COMPONENT 07: COMPULSORY

Applied Mathematics

(15 CREDITS)

Want to understand Newtonian Dynamics? Interested in developing applications of mathematical ideas to study it? Enhance your skills and knowledge in the context of fundamental physical ideas that have been central to the development of mathematics. Analyse aspects of technology and gain experience in the use of computer packages.

View Applied Mathematics on our Module Directory

COMPONENT 08: COMPULSORY

Mathematics Careers and Employability

(0 CREDITS)

What skills do you need to succeed during your studies? And what about after university? How will you realise your career goals? Develop your transferable skills and experiences to create your personal profile. Reflect on and plan your ongoing personal development, with guidance from your personal advisor within the department.

View Mathematics Careers and Employability on our Module Directory

COMPONENT 01: COMPULSORY

Real Analysis 1

(15 CREDITS)

How do you use quantifiers in analysis? What are the principles underlying proofs of basic theorems concerning limits, continuity and differentiability? Gain an understanding into real analysis, examining sequences and functions. Study relevant theorems (like Rolle’s and the Mean Value) and learn to reproduce elementary epsilon-delta arguments.

View Real Analysis 1 on our Module Directory

COMPONENT 02: COMPULSORY

Vector Calculus

(15 CREDITS)

How do you define gradient, divergence and curl? Study the classical theory of vector calculus. Develop the two central theorems by outlining the proofs, then examining various applications and examples. Understand how to apply the ideas you have studied.

View Vector Calculus on our Module Directory

COMPONENT 03: COMPULSORY

Statistics II

(15 CREDITS)

In this module you'll be introduced to the basics of probability and random variables. Topics you will discuss include distribution theory, estimation and Maximum Likelihood estimators, hypothesis testing, basic linear regression and multiple linear regression implemented in R.

View Statistics II on our Module Directory

COMPONENT 04: COMPULSORY

Ordinary Differential Equations

(15 CREDITS)

The subject of ordinary differential equations is a very important branch of Applied Mathematics. Many phenomena from Physics, Biology, Engineering, Chemistry, Finance, among others, may be described using ordinary differential equations. To understand the underlying processes, we have to find and interpret the solutions to these equations. The last part of the module is devoted to the study of nonlinear differential equations and stability. This module provides an overview of standard methods for solving single ordinary differential equations and systems of ordinary differential equations, with an introduction to the underlying theory.

View Ordinary Differential Equations on our Module Directory

COMPONENT 05: COMPULSORY

Linear Algebra

(15 CREDITS)

How do you prove simple properties of linear space from axioms? Can you check whether a set of vectors is a basis? How do you change a basis and recalculate the coordinates of vectors and the matrices of mapping? Study abstract linear algebra, learning to understand advanced abstract mathematical definitions.

View Linear Algebra on our Module Directory

COMPONENT 06: COMPULSORY

Abstract Algebra

(15 CREDITS)

The module introduces you to the key abstract algebraic objects of groups, rings and fields and develops their fundamental theory. The theory will be illustrated and made concrete through numerous examples in settings that you will already have encountered.

View Abstract Algebra on our Module Directory

COMPONENT 07: OPTIONAL

(30 CREDITS)

COMPONENT 08: COMPULSORY

Mathematics Careers and Employability

(0 CREDITS)

View Mathematics Careers and Employability on our Module Directory

COMPONENT 01: COMPULSORY

Complex Variables and Applications

(15 CREDITS)

Can you identify curves and regions in the complex plane defined by simple formulae? How do you evaluate residues at pole singularities? Study complex analysis, learning to apply the Residue Theorem to the calculation of real integrals.

View Complex Variables and Applications on our Module Directory

COMPONENT 02: COMPULSORY

Capstone Project: Mathematics

(15 CREDITS)

This module will allow you to step out of the classroom and gain real experience in your selected branch of Mathematics that you could not gain from a lecture. You will be able to develop your ability to work independently on research and produce a project report on your topic of interest.

View Capstone Project: Mathematics on our Module Directory

COMPONENT 03: OPTIONAL

(45 CREDITS)

COMPONENT 04: OPTIONAL

(45 CREDITS)

COMPONENT 05: COMPULSORY

Mathematics Careers and Employability

(0 CREDITS)

View Mathematics Careers and Employability on our Module Directory

COMPONENT 01: CORE

Advanced Capstone Project: Actuarial Science, Data Science or Mathematics

(30 CREDITS)

Our Advanced Capstone Projects are opportunities for students to study independently a topic in mathematics, statistics and related areas (such as mathematical physics, data science, modelling and so on) and develop skills such as writing reports and giving presentations. You will be monitored by a supervisor, who will periodically set tasks and discuss the progress of the work. The key purpose of Advanced Capstone Projects is that you should be given the opportunity to show your strengths and be allowed a certain amount of freedom and leeway in how you complete the project. It will also provide opportunities for you to develop transferable communication, time- and task-management skills, through researching the topic and organising and producing the written and oral reports.

View Advanced Capstone Project: Actuarial Science, Data Science or Mathematics on our Module Directory

COMPONENT 02: COMPULSORY

Research Methods

(15 CREDITS)

Looking to build your research capabilities? This module will equip you with the principal research tools for your postgraduate course in Mathematical Sciences, including practice in the mathematical word-processing language LaTeX.

View Research Methods on our Module Directory

COMPONENT 03: COMPULSORY

Machine Learning

(15 CREDITS)

Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.

View Machine Learning on our Module Directory

COMPONENT 04: COMPULSORY

Modelling Experimental Data

(15 CREDITS)

Can you calculate confidence intervals for parameters and prediction intervals for future observations? Represent a linear model in matrix form? Or adapt a model to fit growth curves? Learn to apply linear models to analyse data. Discuss underlying assumptions and standard approaches. Understand methods to design and analyse experiments.

View Modelling Experimental Data on our Module Directory

COMPONENT 05: OPTIONAL

(45 CREDITS)

Teaching

Courses are taught by a combination of lectures, laboratory work, assignments, and individual and group project activities
Group work
A significant amount of practical lab work will need to be undertaken for written assignments and as part of your learning

Assessment

You are assessed through a combination of written examinations and coursework
All our modules include a significant coursework element
You receive regular feedback on your progress through in-term tests
Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework

Fees and funding

Home/UK fee

£9,250

International fee

£17,700

EU students commencing their course in the 2021-22 academic year will be liable for the International fee.

Fees will increase for each academic year of study.

Home/UK fees and funding information

International fees and funding information

What's next

Our events are a great way to find out more about studying at Essex. We run a number of Open Days throughout the year which enable you to discover what our campus has to offer. You have the chance to:

tour our campus and accommodation
find out answers to your questions about our courses, student finance, graduate employability, student support and more
meet our students and staff

Check out our Visit Us pages to find out more information about booking onto one of our events. And if the dates aren’t suitable for you, feel free to book a campus tour here.

2021 Open Days (Colchester Campus)

Saturday, August 14, 2021

Saturday, September 18, 2021

Saturday, October 23, 2021

Find out more

How to apply during Clearing

Once you’ve checked that we have the right course for you, applying couldn’t be simpler. Fill in our quick and easy Clearing application form with as much detail as you can. We’ll then take a look and get back to you with a decision. There’s no need to call us to apply; just do it all online.

Find out more about Clearing

Interviews

We don’t interview all applicants during Clearing, however, we will only make offers for the following course after a successful interview:

BA Multimedia Journalism
BSc Nursing (Adult)
BSc Nursing (Mental Health)
BA Social Work

The interview allows our academics to find out more about you, and in turn you’ll be able to ask us any questions you might have. Further details will be emailed to you if you are shortlisted for interview.

Apply now

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