Data Science MSci/BSc (Hons)

 

Course Code

UCAS Code: BSc - 256A
UCAS Code: MSci - 257A
International Code: EECU042 (Bsc)
International Code: EECU043 (MSci)

Location

Coventry University (Coventry)

 

Study mode

Full-time
Sandwich

Duration

3 years full-time
4 years full-time
4 years sandwich
5 years sandwich

Start date

September 2022

How to apply
Book an Open Day
Download a prospectus
Register for updates

Course overview

Study level: Undergraduate

Ninety percent of the data in the world today has been created in the last two years alone, rendering traditional data processing applications inadequate and increasing the demand for sophisticated data analysts who can collate, interpret, and draw value from complex data sets.

Responding to this trend, our new integrated master’s course brings together a range of mathematical, statistical, and computational techniques, which incorporate probability, predictive analytics, and advanced modelling to extract value and make sense of multiple sets and large amounts of data. As an integrated undergraduate and postgraduate course, you can graduate at master’s Level.

Businesses and organisations from almost every sector have woken up to the power of data analytics. Used effectively, they can inform decision making within business and finance, predict and dispense medical treatment within the healthcare system and help improve performance in sports or interpret data from smartphone apps.

Throughout your studies, you will have opportunities to participate in a series of skills development sessions to improve your digital literacy, as well as presentation and writing skills, particularly in a mathematical context. We will familiarise you with a range of computational software related to the fields of mathematics and statistics, such as R, SPSS, LaTeX, Excel, Matlab, Python, Maple and Minitab.

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Global Ready

An international outlook, with global opportunities
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Teaching excellence

Taught by lecturers who are experts in their field
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Employability

Career ready graduates, with the skills to succeed

Why you should study this course

A diverse range of sectors, such as the IT industry, health, sports, finance, marketing, and sales, require graduates with the ability to think clearly and logically, analyse complicated data sets, solve problems, make recommendations and communicate technical information in a language everyone can understand.

A good grounding in mathematical thinking, statistics and computing is essential for creating and using algorithms and systems that identify patterns and extract value from masses of data.

Coventry University has a long tradition of teaching mathematics, statistics, and computing with a strong emphasis on its applications in practical situations. This new course blends all these subject areas with a view to tackling a huge variety of interesting and engaging problems from business and industry – from fraud detection and credit risk to efficiency improvements and optimisation of delivery methods.

You’ll have access to our modern computing facilities, which enable you to gain experience using mathematical software packages, like MAPLE and MATLAB®. You can also receive one-to-one assistance from sigma, the university’s internationally-renowned Centre for Excellence in Mathematics and Statistics Support.

What you'll study

The first year lays the foundation of the mathematical and computational foundations on which the rest of the course builds, with an introduction to computing, data structures, probability, and exploratory data analysis.

Modules

  • This module builds a foundation for the study of statistics. It provides a foundational study of probability, and then builds on this to develop the necessary theory, methods and concepts that are needed to study statistics at a higher level.

    Compulsory

  • This module provides core algebra for those undertaking degrees in the mathematics area. The aim of this module is to consolidate the different A levels and equivalent qualifications, and develop the material studied there to provide the underpinning for Year 2 modules.

    Compulsory

  • This module provides core calculus for those undertaking degrees in the mathematics area. The primary aim of this module is to consolidate the material covered in the different A levels and equivalent qualifications, explore some of the advanced concepts needed for an extensive study of mathematics required for study in Year 2.

    Compulsory

  • This module introduces the fundamentals of computer programming and algorithm construction that will underpin the technical and theoretical content of undergraduate degree courses based within the discipline of Computing.

    Compulsory

  • The purpose of this module is to equip you with the concepts of software-based system development and principles of software design used by industry. It provides a practical guide to the software development process with associated tools and techniques.

    Compulsory

  • This module gives you the necessary skills to become a confident and independent learner and develop your professional competencies, including personal development planning, and mathematical programming.

    Compulsory

  • You will also be able to take an Add+vantage module which can allow you to develop your CV by taking credits in an area of study that doesn’t have to be related to your degree. The assessment type will depend on the type of Add+vantage module you wish to take.

    Compulsory

    Assessment: Coursework and exam

The second year deepens your knowledge in mathematical and computational modules including further algebra, calculus, and statistical computing.

Modules

  • The primary aims of the module are to provide underpinning mathematical methods and an introduction to abstract algebra (including some number theory), providing a first serious exposure to axiomatically defined mathematical structures and showing how they can be applied to combinatorial problems.

    Compulsory

  • R is a statistical programming language and SPSS is a statistical software package, both of which are widely used in local authorities, universities, and business. This module aims to introduce you to R and SPSS and give you the skills and confidence to use both packages competently and professionally for data analysis.

    Compulsory

  • This module provides an insight into how data and information retrieval systems are designed. It provides a study of database concepts, theory, and design with some practical use of database and information retrieval tools and techniques.

    Compulsory

  • This module will introduce two of the most used statistical techniques, multiple regression and analysis of variance (ANOVA). The ideas of statistical inference and statistical modelling will be thoroughly explored and expanded. A statistical package will be used throughout.

    Compulsory

  • This module provides the focus for you to continue developing your professional competencies including personal development planning and reflection, independent learning, report writing, and presentation skills.

    Compulsory

  • You will also be able to take an Add+vantage module which can allow you to develop your CV by taking credits in an area of study that doesn’t have to be related to your degree. The assessment type will depend on the type of Add+vantage module you wish to take.

    Compulsory

    Assessment: Coursework and exam

  • One from the following:

    • Discrete Mathematics – 20 credits
      This module intends to introduce basic facts on discrete Mathematics and Stochastic processes.
    • Software Engineering – 20 credits
      This module investigates the software quality processes associated with the production of a large-scale software development. You should learn the tools and techniques appropriate to contribute to the development of a solution to a real-world problem.
    • Operational Research Techniques – 20 credits
      Operational Research concerns the application of certain mathematical methods that are useful for solving a variety of decision-making problems. The techniques developed also aim to improve the efficiency of processes and management of complex systems.

    Compulsory

Following your second year, you will have an option to apply for a one-year professional work placement or study abroad in a partner institution.

If you wish to undertake the optional study abroad/placement year, you will take either the Placement Year module or the Study Abroad Year module which both typically run for a full academic year between years 2 and 3 of your course. You are normally able to progress onto the relevant module if you have successfully completed the first two years of the course (i.e. having accumulated 240 credits) and have a confirmed opportunity two weeks prior to the start of the academic year, however we encourage international students to confirm their placements earlier to ensure they are able to meet any applicable visa requirements.

Students opting for either the work placement or study abroad will take an academic module in which they reflect on their experiences. The module appears on a student’s transcript as a zero credit module. They will be supported by the university’s Talent Team throughout the process and will be allocated a tutor who will keep in touch. 

In the third year, you should continue to deepen your specialist knowledge and engage in a dissertation project, carrying out in-depth data analysis in a field that interests you. Recent project topics have included modelling of football data, medical data and environmental data, forecasting wine sales and credit risk modelling.

Modules

  • This module represents an introduction to the wide field of machine learning. It will present fundamental concepts related to supervised and unsupervised learning methods, for example linear regression, support vector machines, radial basis function, decision trees and random forests, clustering techniques and naïve Bayes classification models.

    Compulsory

  • This module aims to enable you to learn the theory of computer simulation and process modelling, how it is used, tools and techniques for logic modelling for solving of real-life problems.

    Compulsory

  • This module forms a major individual study at the honours level in areas related to mathematics, applied mathematics or statistics.

    Compulsory

  • The aim of this module is to develop your practical mathematics skills to a level expected of a modern graduate through investigation of an advanced topic in mathematics, and to prepare you for future employment or postgraduate study.

    Compulsory

  • Two from the following:

    • Cryptography and Information Theory – 20 credits
      This module provides you with a fundamental knowledge of contemporary mathematical communication theory, ranging from entropy as a measure of information, through robust methods of encoding data via error correcting codes, to means of making messages secure by encryption.
    • Optimisation – 20 credits
      This module discusses the mathematics behind optimisation problems with discrete and continuous variables and with as well as without constraints.
    • Advanced Topics in Statistics – 20 credits
      This module introduces several important topics in the areas of advanced statistics, and where appropriate, relevant statistical software will be used.

    Compulsory

  • You will also be able to take an Add+vantage module which can allow you to develop your CV by taking credits in an area of study that doesn’t have to be related to your degree. The assessment type will depend on the type of Add+vantage module you wish to take.

    Compulsory

    Assessment: Coursework and exam

The MSci offers you in-depth knowledge in artificial intelligence that can be applied in data science, for example Machine Learning or Artificial Neural Networks.

Modules

  • This module considers various aspects of Markov chain models and their real-world applications using relevant software.

    Compulsory

  • This module provides you with an introduction to machine learning techniques, the associated concepts and applications.

    Compulsory

  • The aim of this module is to give you an introduction to evolutionary algorithms and fuzzy logic from an application-oriented standpoint.

    Compulsory

  • This module will introduce you to the concepts used in neural networks and their application in solve real-world problems.

    Compulsory

  • In this module, you will be exposed to a range of information retrieval techniques, from theory and context to application and implementation.

    Compulsory

  • This module aims to introduce you to the current management and visualisation methods for Big Data. Cutting edge techniques will be taught which will enable you to discover patterns, relationships, and associations in big data sets.

    Compulsory

  • In this preparatory module, you will identify a suitable topic of study and project supervisor. You will then exercise and extend their skills in gathering, understanding, and critically evaluating literature; assessing and acting on relevant ethical and legal issues; and applying planning processes for the undertaking of a significant piece of work.

    Compulsory

  • The Individual Research Project is a substantial piece of research into an area of study chosen by you, under guidance from a supervisor and with relevance to your degree course.

    Compulsory

We regularly review our course content, to make it relevant and current for the benefit of our students. For these reasons, course modules may be updated.

How you'll learn

Throughout the course, great emphasis is placed on practical skills development. Some of your time will be spent on computer laboratory sessions, which may involve the use of mathematical software to solve mathematical problems, and we also run examples classes to review and discuss solutions to exercises.

You may have opportunities to work with staff on real-world problems from industry, commerce, and research groups, as you would in professional practice. This means that you have the opportunity to develop professional skills at the same time as you learn the technical content of your degree.

In a typical week, your class time will be divided amongst:

  • Personal tutorials and small group teaching
  • Medium group teaching (for example seminars, tutorial sessions, lab sessions and workshops)
  • Large group teaching (lectures).

In addition, you will be expected to undertake significant self-directed study each week, depending on the demands of individual modules. The number of hours of class time will vary from year to year: it’s likely to be around 18 hours contact per week in the first year (around six hours per week per module) dropping to around 12 (around 4 hours per week per module) in final year as you become a more independent learner.

Assessment

This course will be assessed using a variety of methods which could vary depending upon the module. Assessment methods include formal examinations, essays, coursework, tests, group work and practical work, for example presentations and tests.

The Coventry University Group assessment strategy ensures that our courses are fairly assessed and allows us to monitor student progression towards the achieving the intended learning outcomes.

Job ready

On successful completion, you should have knowledge of:

  • The logical construction of a mathematical argument.
  • The application of mathematics to construct models and their resolution, with an appreciation of the validity of the model and the use of approximation.
  • The use of a range of analytic and descriptive techniques.
  • The strengths and weaknesses of selected mathematical software and selected programming or scripting languages and their use to extend capabilities.
  • A range of real-world applications of mathematics, statistics and data analytics techniques, some set in an international context.

On successful completion, you should be able to:

  • Understand, reproduce, and generalise logical mathematical reasoning.
  • Organise and interpret information and results from mathematical models.
  • Analyse problems and construct an appropriate formulation and solution with relatively little guidance or support.
  • Use specialist modern information technology packages and programming language confidently.
  • Use a wide range of information resources to acquire relevant information.

International experience opportunities

If you have a desire to gain international experience it is possible to spend a year studying abroad*. In the past, students have chosen to study Mathematics in St Marcus University in California, University of Malta, Stockholm University in Sweden, also universities in the Netherlands, Germany, and Australia. Courses in all these universities are delivered in English.

We can support you in finding an internship in many countries across the globe and support you in seeking financing for that experience. Past students have gone to work in countries such as Malaysia, Belgium, and Spain.

Entry requirements

Typical offer for 2022 entry.

Requirement What we're looking for
A level BSc: BBB to include Mathematics at grade B or above. Excludes General Studies.
MSci: ABB to include Mathematics at grade B or above. Excludes General Studies.
GCSE Minimum 5 GCSEs at grade 9-4 including English and Mathematics, or specified equivalents.
BTEC Assessed on an individual basis.
International Baccalaureate Diploma Programme 31 points to include 5 points in Mathematics at Higher Level.

We recognise a breadth of qualifications, speak to one of our advisers today to find out how we can help you.

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Select your region to find detailed information about entry requirements:

Europe

Americas

Middle East

South Asia

South East Asia

East Asia

Africa

Russia and Central Asia

You can view our full list of country specific entry requirements on our Entry requirements page.

Alternatively, visit our International hub for further advice and guidance on finding in-country agents and representatives, joining our in-country events and how to apply.

English language requirements

  • IELTS: 6.0 overall, with no component lower than 5.5.

If you don't meet the English language requirements, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course. 

For more information on our approved English language tests visit our English language requirements page.

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Fees and funding

2022/23 Tuition fees

Student Full time Part time
UK £9,250 per year Not available
International £18,050 per year Not available

For advice and guidance on tuition fees and student loans visit our Undergraduate Finance page and see The University’s Tuition Fee and Refund Terms and Conditions.

We offer a range of International scholarships to students all over the world. For more information, visit our International Scholarships page.

Tuition fees cover the cost of your teaching, assessments, facilities and support services. There may be additional costs not covered by this fee such as accommodation and living costs, recommended reading books, stationery, printing and re-assessments should you need them. Find out what's included in your tuition costs.

Facilities

The faculty of Engineering, Environment and Computing boasts modern, multifunctional teaching and research buildings that support hands-on learning. Laboratories and workshops are equipped to commercial and industrial standards and are available to students both in and out of class time (subject to availability).

Informal study areas

Informal study areas

You will have plenty of computer access to all the specialist software required for your studies. There are also bookable spaces where students can meet with academics or work in small groups.
 

sigma centre

sigma Centre

The sigma Centre is an award-winning mathematics support centre, which provides a wide range of learning resources in mathematics and statistics. Students can make use of drop-in sessions or one-to-one appointments.

maths laboratory

Mathematics laboratory

Set out like a traditional classroom with a large whiteboard, it is the only teaching room in the Engineering and Computing Building laid out in this way, designed to suit the teaching style required for this subject.

Careers and opportunities

Data analysts have job prospects in areas such as business analysis, risk analysis, energy demand forecasting, health analytics, sports analytics, web analytics, games data analytics, social media analytics and many, many more.

How to apply

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Your next steps

Student life
Accommodation
Fees and funding

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  • Student Contract

    By accepting your offer of a place and enrolling with us, a Student Contract will be formed between you and the university. A copy of the 2021/22 Contract can be found here. The Contract details your rights and the obligations you will be bound by during your time as a student and contains the obligations that the university will owe to you. You should read the Contract before you accept an offer of a place and before you enrol at the university.

    Tuition fees

    The tuition fee for the course that is stated on the course webpage and in the prospectus for the first year of study will apply. We will review our tuition fees each year. For UK and EU students, if Parliament permit an increase in tuition fees, we may increase fees for each subsequent year of study in line with any such changes. Note that any increase is expected to be in line with inflation. Following the UK’s exit from the European Union, EU students should be aware that there may be a change to UK laws following the UK’s exit, this may change their student status, their eligibility to study part time, and/or their eligibility for student finance. We will act in accordance with the UK’s laws in force in relation to student tuition fees and finance from time to time.

    For International students the tuition fee that is stated on the course webpage and in the prospectus for the first year of study will apply. We will review our tuition fees each year. For international students, we may increase fees for each subsequent year of study but such increases will be no more than 5% above inflation.

    Accreditations

    The majority of our courses have been formally recognised by professional bodies, which means the courses have been reviewed and tested to ensure they reach a set standard. In some instances, studying on an accredited course can give you additional benefits such as exemptions from professional exams (subject to availability, fees may apply). Accreditations, partnerships, exemptions and memberships shall be renewed in accordance with the relevant bodies’ standard review process and subject to the university maintaining the same high standards of course delivery. 

    Facilities

    Facilities mentioned on this page may not be relevant for every course. Due to the ongoing restrictions relating to COVID-19, some facilities (including some teaching and learning spaces) and some non-academic offerings (particularly in relation to international experiences), may vary from those advertised and may have reduced availability or restrictions on their use.

    Placements and study abroad opportunities

    Please note that we are unable to guarantee any placement or study abroad opportunities and that all such opportunities may be subject to additional costs (e.g. travel, visas and accommodation etc.), competitive application, availability and/or meeting any applicable visa requirements. To ensure that you fully understand the requirements in this regard, please contact the International Office for further details if you are an EU or International student.

    Additional costs

    This course may incur additional costs associated with any field trips, placements or work experience, study abroad opportunities or any other opportunity (whether required or optional), which could include (but is not limited to), equipment, materials, bench fees, studio or facilities hire, travel, accommodation and visas).