Data Science

UCAS code: I245

Here's what University of Chester says about its Data Science course.

As data science continues to revolutionise industries, the demand for skilled graduates is soaring. Our Data Science degree ensures you're not just up-to-date with these advancements but ahead of the curve. The course aims to equip you with cutting-edge skills in R, Python, SQL, and Power BI, essential for analysing and modelling data effectively, efficiently, and ethically.

You’ll learn to harness these technologies to drive innovative and informed decisions across diverse sectors, including business, finance, politics, and healthcare. Develop your proficiency in analytical languages and visualisation tools to transform complex data into actionable insights and business plans that are accessible to both management and non-specialists.

Opting for a degree with a Placement Year provides you with the invaluable opportunity to undertake a professional placement at the end of your second year. This immersive experience allows you to apply your academic knowledge in a real-world setting, gain practical insights into the workplace, and build essential connections for your future career.

By integrating hands-on experience with your studies, you’ll enhance your skills, broaden your professional network, and increase your employability, setting you up for success in the competitive data science field.

The BSc Data Science course contains core modules at each level of study. At level 4, you are introduced to the fundamental and professional skills required to study a computing programme. These fundamental skills are complemented by introductory practical and programming skills, including aspects of user experience.

Level 5 builds on this foundation allowing you to develop your programming skills along with specific skills in data science including machine learning the application of probability and statistics to data science, you will get to put skills into practice in a work-based learning module towards the end of this year. You can also opt to take a year in industry before progressing to level 6.

The final year allows you to include more diversity in your programme by selecting a module from areas such as mathematics, cybersecurity or software engineering. You will also work on a final-year data science project under the supervision an academic staff member.

The information listed in this section is an overview of the academic content of the course that will take the form of either core or option modules and should be used as a guide. We review the content of our courses regularly, making changes where necessary to improve your experience and graduate prospects. If during a review process, course content is significantly changed, we will contact you to notify you of these changes if you receive an offer from us.

This course is delivered in three terms of ten weeks each. In each term, students study 40 credits comprised of either one or two modules. Scheduled contact hours range between approximately 6 and 12 hours per week depending upon the level of study and the complexity of the material being taught.

This course is delivered primarily through in-person learning supported by online learning materials. Students can expect to take part in labs, workshops, lectures and tutorials. Teaching will be delivered by experienced academics and practitioners in the subject. This will be supplemented by occasional guest lecturers and speakers.

On this course, you should expect to spend an average of 30 – 34 hours per week on independent study which might include following asynchronous learning material on the University’s VLE, using the University’s library, working with peers, and preparing work for assessment.

There will be a broad range of assessment methods so that students are exposed to the different types of tasks they might encounter in the workplace. These will include coursework in the form of programming projects, software artefacts, portfolios of work, written work (e.g. essays) and presentations. In some modules, students will encounter class tests and practical assessments. We continuously review the assessment methods used in order that they adequately prepare students for graduate-level employment.