Course summary
Data scientists/analysts are in demand across a large range of sectors, from healthcare to finance, from marketing to transport. This course aims to provide the essential training you will need to be successful in this fast-moving, dynamic field. The course brings together a range of techniques that the modern data scientist needs. You will study modules in mathematics, data analysis and computing and tackle a variety of interesting and engaging problems from the latest research studies, business and industry. Key Course Benefits • You will have the chance to equip yourself with transferable and professional skills which prepare you for employment in industry, business, or education. • You will be provided with the opportunity to develop critical and reflective skills required for problem solving in a wide variety of contexts. • The course has a particular emphasis on modern applications and the use of appropriate computational methods, software and technology. • You can expect to improve your knowledge and understanding of the theory and practice of the latest data science, as well as the use of computational methods. • You will have the chance to gain industry-relevant experience* as you apply real-world, commercial software development practices within teams of your peers, preparing you for your career after graduation. *UK and international opportunities Please note that we are unable to guarantee any UK or International opportunities (whether required or optional) such as internships, work experience, field trips, conferences, placements or study abroad opportunities and that all such opportunities may be subject to additional costs (which could include, but is not limited to, equipment, materials, bench fees, studio or facilities hire, travel, accommodation and visas), competitive application, availability and/or meeting any applicable travel COVID and visa requirements. To ensure that you fully understand the visa requirements, please contact the International Office.
Modules
Year One In your first year, you will be taught the fundamental skills and concepts needed to begin your journey as a data scientist. You’ll be familiarised with the mathematical, statistical and computational foundations, and you will apply those principles in regular laboratory sessions which help solidify your understanding. You will also begin developing the professional skills you will need in your day-to-day career on graduation: working as part of a team, the ethical and legal issues around data structure and models. Modules Calculus - 20 credits Algebra - 20 Credits Programming: Concepts and Algorithms - 20 Credits Working with Data - 20 Credits Programming: Professional Practice - 20 Credits Probability and Statistics - 20 Credits Year Two In year two, you will develop more advanced knowledge and skills to do with data science, linear statistical models and artificial intelligence, amongst others. Modules Artificial Intelligence - 20 Credits Linear Algebra and Differential Equations - 20 Credits Advanced Algorithms - 20 Credits Data Science - 20 Credits Linear Statistical Models - 20 Credits Data Science Group Project - 20 Credits Placement Year There’s no better way to find out what you love doing than trying it out for yourself, which is why a work placement* can often be beneficial. Work placements usually occur between your second and final year of study. They’re a great way to help you explore your potential career path and gain valuable work experience, whilst developing transferable skills for the future. If you choose to do a work placement year, you will pay a reduced tuition fee* of £1,250. For more information, please go to the fees and funding section. During this time, you will receive guidance from your employer or partner institution, along with your assigned academic mentor who will ensure you have the support you need to complete your placement. Final Year The final stage of the BSc (Hons) in Data Science covers advanced topics in data science including Big Data management and visualisation methods, machine learning algorithms, Artificial Neural Networks and advanced statistical methods. Modules Data Visualisation - 20 Credits Statistical methods for Data Science - 20 Credits Machine Learning - 20 Credits Project Discovery - 20 credits Dissertation and Project Artefact - 20 credits Optional Modules Additional Year The additional fourth year master's option will deepen your knowledge and expertise*. This year provides insight into more advanced topics in data science and can act as a stepping stone to postgraduate research or further study. 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. Before accepting any offers, please check the website for the most up to date course content. For full module details please check the course page on the Coventry University website. *For further information please check the course page on the Coventry University website
Assessment method
This course will be assessed using a variety of methods which will vary depending upon the module. Assessment methods include: Formal examinations Phase tests Essays Group work Presentations Reports Projects Coursework Exams Individual Assignments The Coventry University Group assessment strategy ensures that our courses are fairly assessed and allows us to monitor student progression towards achieving the intended learning outcomes.
How to apply
This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.
Application codes
Please select a course option – you will then see the application code you need to use to apply for the course.
Points of entry
The following entry points are available for this course:
- Year 1
Entry requirements
Qualification requirements
UCAS Tariff - 128 points
A level - ABB
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
Access to HE Diploma
Scottish Higher - ABCCC
International Baccalaureate Diploma Programme - 31 points
GCSE/National 4/National 5
All applications are considered on an individual basis and the whole application is reviewed which includes previous and predicted qualifications, experience, reference and your motivation to study the course. The University also accepts the BTEC Level 3 National Extended Certificate / BTEC Level 3 Subsidiary Diploma and BTEC Level 3 National Diploma / BTEC Level 3 Diploma for entry onto degree programmes, provided that they are studied in combination with other qualifications that total the equivalent of three A2 Levels. This may include subject specific requirements where necessary. If you are successful in receiving an offer, you will be invited to attend an Applicant Visit Day to discover more about the course and studying at Coventry University.
Student Outcomes
There is no data available for this course. For further information visit the Discover Uni website.
Fees and funding
Tuition fees
England | £9250* | Year 1 |
Northern Ireland | £9250* | Year 1 |
Scotland | £9250* | Year 1 |
Wales | £9250* | Year 1 |
Channel Islands | £9250* | Year 1 |
Republic of Ireland | £9250* | Year 1 |
*This is a provisional fee and subject to change.
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Provider information
Coventry University
Priory Street
Coventry
CV1 5FB