Coventry University
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.
Coventry, United Kingdom
36 Months
£ 18,050
IELTS: 6
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:
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:
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.
Requirement |
What we're looking for |
---|---|
A level |
BSc: BBB 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. |
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.