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
If you meet the criteria, you could choose to take an additional fourth year master's option, which 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 methods

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.

Tuition fees

Select where you currently live to see what you'll pay: