Data Science MSci/BSc (Hons)

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
 
Year one

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
 

• Statistics - 20 credits

  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
   

• Algebra - 20 credits

  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
   

• Calculus - 20 credits

  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
   

• Programming and Algorithms - 20 credits

  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
   

• Software Design - 20 credits

  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
   

• Professional and Academic Skills 1 - 10 credits

  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
   

• Add+vantage – 10 credits

  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
   

Year two

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

Modules
 

• Further Algebra and Calculus - 20 credits

  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
   

• Statistical Computing - 20 credits

  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
   

• Data Science - 20 credits

  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
   

• Linear Statistical Models - 20 credits

  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
   

• Professional and Academic Skills 2 - 10 credits

  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
   

• Add+vantage – 10 credits

  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
   

• Optional modules
   

  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
   

Placement year

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. 

Final year

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
 

• Machine Learning and Related Applications - 20 credits

  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
   

• Business Simulation - 20 credits

  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
   

• Project - 20 credits

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

  Compulsory
   

• Professional and Academic Skills 3 - 10 credits

  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
   

• Optional modules
   

  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
   

• Add+vantage – 10 credits

  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
   

Additional year

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
 

• Markov Chains - 15 credits

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

  Compulsory
   

• Machine Learning - 15 credits

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

  Compulsory
   

• Evolutionary and Fuzzy Systems - 15 credits

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

  Compulsory
   

• Artificial Neural Networks - 15 credits

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

  Compulsory
   

• Intelligent Information Retrieval - 15 credits

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

  Compulsory
   

• Big Data Management and Data Visualisation - 15 credits

  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
   

• Individual Research Project Preparation – 15 credits

  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
   

• Individual Research Project – 15 credits

  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

Typical offer for 2022 entry.
 

English language requirements

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

International Fees
£18,050 per year

International Pathways 2022 Scholarship
You could enjoy a £3,000 reduction in tuition fees.

Our high-quality foundation, international year one and pre-masters courses are for international students who do not meet the requirements for direct entry to their preferred Coventry University undergraduate or postgraduate course. We can support you to achieve the academic and/or English grades you need and help you gain the personal and professional skills required to study at university.

We want to encourage ambitious international students like you to study at Coventry University, so we’ve secured extra financial support for you worth £3,000, to help with the cost of tuition fees, living expenses and accommodation.

The scholarship application deadline is:
September 2022 intake: 31 July 2022

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.