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Undergraduate study
Mathematics

Mathematics with Data Analytics
BSc (Hons)

G120 BSc/MDA

 
 

Course overview

Data analysis is rapidly becoming a mission-critical requirement across a range of fields, including policing, security, transportation, fraud and risk detection, business, delivery logistics, internet/web search, healthcare, finance, energy management, social media, and cybersecurity.

You learn the fundamental mathematics and data analysis methods and toolkits to help you apply data analytics to a range of applications and technologies.

Free online maths course
Prepare for your studies with our free online Mathematics for University course. Develop your knowledge and understanding in maths so that you can start your studies in September confidently and better prepared. Places offered on a first-come, first-served basis. Find out more

An optional work placement year is included, at no extra cost. Alongside this, you can gain valuable experience and engagement with the sector through our shorter work placements, internships and work experience opportunities.
Find out more

 

Course details

Year 1 contains an introduction to the main areas of mathematics. In Year 2 you build on these foundations to gain more specialist knowledge and have the opportunity to work on an industrial case-study to apply your knowledge.

Group projects in Year 1 and Year 2 are key to developing your communication skills through independent learning and team work, providing you with practical skills essential to your career. The Year 2 group project allows you to apply your knowledge and build your work experience.

The optional work placement year during Year 3 provides valuable work experience that helps you stand out when applying for your first graduate job. It’s your chance to apply the academic knowledge in a work environment and improve your career prospects. It can even lead to the offer of a permanent job with your placement employer.

The final year is devoted to advanced courses in your specialism and alongside you complete a project in an area of mathematics that interests you. The project provides a unique opportunity to explore a subject in greater depth, guided throughout by your project supervisor.

Course structure

Year 1 core modules

Analysis I

The module gives a solid foundation to the properties of the real numbers and of continuous functions of one real variable. You develop the mathematical skills and techniques of fundamental operations with limits, and develop skills in using mathematical terminology and style of reasoning in order to solve problems.

Lectures introduce techniques and underlying principles. Problem-solving seminars based on weekly worksheets provide the opportunity for you to demonstrate understanding and develop competence in the application of these.

Analysis II

This module deepens your mathematical knowledge in analysis to include the techniques of differentiation and integration in one real variable. The fundamental functions (exp, log, sin, cos, tan) are defined accurately and their properties outlined. Important applications like finding local extrema of functions, approximation through Taylor expansion, or the solution of elementary ODEs is presented, their mathematical eligibility proven, and their execution practised.

Lectures are used to introduce techniques and underlying principles. Problem-solving seminars based on weekly worksheets provide the opportunity for you to demonstrate understanding and develop competence in the application of these.

Linear Algebra 1

This module gives a solid foundation to Linear Algebra topics. You develop the mathematical skills and techniques of fundamental operations of vectors and matrices, and skills in selecting and applying Linear Algebra techniques to solve problems.

Lectures are used to introduce techniques and underlying principles. Problem-solving tutorials provide the opportunity for you to demonstrate understanding and develop competence in the application of these.

Linear Algebra 2

This module deepens your mathematical knowledge in Linear Algebra to include Eigenvalues and Eigenvectors, and extend your base of techniques to solve a variety of problems. The emphasis is on developing competence in the identification of the most appropriate method to solve a given problem and its subsequent application.

Lectures are used to introduce techniques and underlying principles. Problem-solving tutorials provide the opportunity for you to demonstrate understanding and develop competence in the application of these.

Probability and Statistics

You are introduced to the concepts of statistics and probability. You develop a conceptual understanding of basic statistical and probability methods, supported by the use of a statistical computer package.

Lectures are used to introduce techniques and underlying principles. Problem-solving seminars/laboratory sessions provide the opportunity for you to demonstrate understanding and develop competence in the application of these.

Python Programming

You are introduced to the fundamental concepts of software development through the Python programming language.  

You look at key aspects of the software development process including designing solutions, writing application code, developing documentation and formal approaches to testing.

 

Year 2 core modules

Abstract Algebra

This topic, also known as algebra or algebraic structures, broadens the mind to mathematics beyond the common number systems and is crucial for a deeper understanding of many other branches of mathematics such as topology, differential equations, geometry, analysis and number theory. You extend your base of techniques beyond linear algebra to solve a variety of algebraic problems.

Analysis III

This module will extend the mathematical knowledge in Analysis by treating the case of vector-valued functions of several variables and their differentiation and integration. Accordingly, important applications, such as determining local extrema, approximation via Tayler expansion will be discussed, for functions of several variables, and, if appropriate, the vector valued case. The integration theory in several variables will follow the measure-theoretic approach of Lebesgue. Applications of integration theory will include surface integrals, volume integrals, line integrals and sketch their relevance in, e.g., mechanics and electrodynamics.

Artificial Intelligence

This module provides a general introduction to artificial intelligence (AI) with real-world applications around us. This includes the fundamental concepts of AI, common frameworks used in the analysis and design of intelligent systems, generic algorithms used for implementation and major techniques used in problem solving. This module also introduces popular applications of AI (for example, game design, virtual agents, robotics) and benefits of using AI (for example, how to enhance efficiency, productivity and reduce costs).

Mathematical Modelling

You use mathematics as a tool to solve problems using a range of real-world problems to motivate the use of various techniques. Additionally, varying tools are used to implement and calculate solutions. You gain a range of mathematical modelling skills to solve problems.

Lectures are used to introduce principles and concepts. Tutorials involve pen-and-paper as well as computer-based exercises to consolidate and develop your understanding and skills.

Relational and NoSQL Databases

You develop your ability to design and implement database applications to meet business needs. A case study is used to follow the system development life cycle, and you develop a server database application from inception to implementation for a real world scenario.

The module investigates the issues and technologies associated with implementing and supporting databases and the services that are needed to maintain and access a repository of data. Investigations are undertaken in a number of areas including data modelling, data management and approaches that support the modelling and visualisation of data for a range of use views.

Statistical Analysis

This module provides a practical understanding of the useful modelling techniques of regression analysis and analysis of variance. The module instils an understanding and relevance of linear regression models facilitated through the use of a statistical computer package.

Lectures are used to introduce techniques and underlying principles. Problem-solving seminars in IT laboratories provide the opportunity for you to demonstrate understanding and develop competence in the application of these. You are shown how to implement numerical methods using appropriate software tools.

 

Optional work placement year

Work placement

You have the option to spend one year in industry learning and developing your skills. We encourage and support you with applying for a placement, job hunting and networking.

You gain experience favoured by graduate recruiters and develop your technical skillset. You also obtain the transferable skills required in any professional environment, including communication, negotiation, teamwork, leadership, organisation, confidence, self-reliance, problem-solving, being able to work under pressure, and commercial awareness.

Many employers view a placement as a year-long interview, therefore placements are increasingly becoming an essential part of an organisation's pre-selection strategy in their graduate recruitment process. Benefits include:

· improved job prospects
· enhanced employment skills and improved career progression opportunities
· a higher starting salary than your full-time counterparts
· a better degree classification
· a richer CV
· a year's salary before completing your degree
· experience of workplace culture
· the opportunity to design and base your final-year project within a working environment.

If you are unable to secure a work placement with an employer, then you simply continue on a course without the work placement.

 

Final-year core modules

Applied Machine Learning

Machine learning is an important topic in the area of artificial intelligence. The methodology involves building a model of a given task based on observations to make predictions about unseen data. Such techniques are useful when the desired output is known - but an algorithm is unknown, or when a system needs to adapt to unforeseen circumstances. Machine learning draws significantly from statistics and probability theory as (though the applications are many and various) the fundamental task is to make inferences from data samples. The contribution from other areas of computer science is also essential for efficient task representation, learning algorithms, and inferences procedures. You also gain an exposure to a breadth of tasks and techniques in machine learning.

Data Analytics for Enterprise

Business intelligence tools are used to show the state of the business to facilitate better and faster business decision making. The next evolution is business analytics which is a technology-aided process which analyses the data to predict future performance.

You will develop skills in combining the analysis of a given data set from a business case study and the creation of dynamic, interactive visualisations that enable decision makers to explore the data through a variety of perspectives.

Using an interactive graphic gives the option to zoom in on sections of the data which are of interest, explore more than one dimension at a time, and sort and filter to discover new patterns and themes within the data.

Mathematical Data Science

The module introduces mathematical techniques for the processing and analysing massive datasets. In particular, the module discusses how to pre-process and store massive datasets and to design efficient algorithms.

Operations Research

This module is designed to develop?awareness and understanding of operational research methods applicable to analysis of financial and economic data.? Further, the module will introduce numerical optimisation theories and processes and afford the student opportunity to develop theoretical and applied knowledge in optimisation problems within the financial domain.

Project

This module extends the development of independent learning skills by allowing you to investigate an area of engineering or technology for an extended period.

You receive training in writing technical reports for knowledgeable readers and you produce a report or dissertation of the work covered. In addition, you give an oral presentation, a poster presentation or both. The topic can be in the form of a research project or a design project.

You develop key skills in research, knowledge application and creation through keynote lectures where appropriate and self-managed independent study. Support is provided through regular tutorial sessions.

 

Modules offered may vary.

 

How you learn

The course provides a number of contact teaching and assessment hours (including lectures, tutorials, laboratory work, projects, examinations), but you are also expected to spend time working independently. This self-study time is to review lecture notes, solve tutorial exercises, prepare coursework assignments, work on projects and revise for examinations. Your programme also includes a substantial final-year research-based project.

One module in each year of your study involves a compulsory one-week block delivery period. This intensive problem-solving week provides you with an opportunity to focus your attention on particular problems and enhance your team-working and employability skills.

There is a range of extra-curricular mathematics related activities organised by the course team to support your learning including a maths club, invited speeches from academics and industry experts.

How you are assessed

You are assessed on your subject knowledge, independent thought and skills acquisition, through coursework assignments, group presentations, project reports and formal examinations. We use end exams within a number of modules in each year. And we provide an assessment schedule with assessment details and submission deadlines to help with your time management.

You are given tutor feedback during scheduled taught sessions on a regular basis.


Our Disability Services team provide an inclusive and empowering learning environment and have specialist staff to support disabled students access any additional tailored resources needed. If you have a specific learning difficulty, mental health condition, autism, sensory impairment, chronic health condition or any other disability please contact a Disability Services as early as possible.
Find out more about our disability services

Find out more about financial support
Find out more about our course related costs

 
 

Entry requirements

Entry requirements

Typical offers are made in the range of 96-112 points from any combination of recognised Level 3 qualifications or equivalent, including mathematics.

The most common acceptable Level 3 qualifications are:

  • A levels (grades BBC, including at least C in mathematics)
  • BTEC Extended Diploma (DMM, including merit or distinction in mathematics units)
  • Access to HE Diploma (with merit or distinction in at least 12 level 3 credits in mathematics).

If the qualification you are studying is not listed, please contact our admissions office for advice. We accept many alternative UK and international qualifications.

International students who need a student visa to study in the UK should check our web pages on UKVI-compliant English language requirements. The University also provides pre-sessional English language courses if you do not meet the minimum English language requirement.

For general information please see our overview of entry requirements

International applicants can find out what qualifications they need by visiting Your Country


You can gain considerable knowledge from work, volunteering and life. Under recognition of prior learning (RPL) you may be awarded credit for this which can be credited towards the course you want to study.
Find out more about RPL

 

Employability

Career opportunities

All programmes incorporate employability skills development alongside your degree. Our staff utilise their extensive business connections to provide many and varied opportunities to engage with potential employers through fairs, guest lectures, live projects and site visits. In addition we offer a series of workshops and events in all years that ensure you are equipped with both degree-level subject knowledge and the practical skills that employers are looking for in new graduate recruits.

Our award-winning careers service works with regional and national employers to advertise graduate positions, in addition to providing post-graduation support for all Teesside University alumni.

The government’s bursaries and scholarships offers for mathematics graduates is an avenue worth pursuing for those who are interested in teaching. Data analysts are in high demand in a number of job sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education.

 

Information for international applicants

Qualifications

International applicants - find out what qualifications you need by selecting your country below.

Select your country:

  
 

Useful information

Visit our international pages for useful information for non-UK students and applicants.

Talk to us

Talk to an international student enrolment adviser

 
 

Full-time

Entry to 2022/23 academic year

Fee for UK applicants
£9,250 a year

More details about our fees

Fee for international applicants
£14,000 a year

More details about our fees for international applicants


What is included in your tuition fee?

  • Length: 3 years (or 4 with a work placement)
  • UCAS code: G120 BSc/MDA
  • Start date: September
  • Semester dates
  • Typical offer: 96-112 tariff points

Apply online (full-time) through UCAS

 

Part-time

2022/23 entry

Fee for UK applicants
£4,500 (120 credits)

More details about our fees

  • Length: 6 years if entering in Year 1, 4 years if entering in Year 2
  • Attendance: Timetable governed
  • Start date: September
  • Semester dates

Apply online (part-time)

 

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Get in touch

UK students

Email: scedtadmissions@tees.ac.uk

Telephone: 01642 738801


Online chat

International students

Email: internationalenquiries@tees.ac.uk

Telephone: +44 (0) 1642 738900


More international contacts

 

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