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.
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, which previously won the prestigious national Times Higher Education award for Outstanding Support for Students in 2011.
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.
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.
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.
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