|Location||United Kingdom, Sheffield|
|Type||Master courses, full-time|
|Nominal duration||1 year|
|Tuition fee||To be confirmed|
Undergraduate diploma (or higher)
2:1 in any subject
The entry qualification documents are accepted in the following languages: English.
Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original.
IELTS: 6.5 with a minimum of 6.0 in each component
At least 2 reference(s) must be provided.
These should be supplied and signed by academic staff at institutions where you have studied previously. They must be presented on the official letter-headed paper of the relevant institution. If you have been out of education for the last two years, you can send one academic reference plus one from your current employer if you wish.
This CILIP-accredited course produces highly employable graduates for a rapidly expanding global job market.
It was developed in collaboration with external organisations across a range of sectors to make sure you gain knowledge and learn skills that employers are looking for.
You’ll learn the theory and the skills you need to support data-driven decision-making in organisations.
The course covers three core areas: data management, data analysis and business insight. You’ll get hands-on experience with data management and analysis.
Industry experts contribute to the course, sharing their experience and talking you through examples of data science in action.
Our graduates are not just technically proficient. They’re also keenly aware of broader issues such as data presentation, privacy and ethics.
That extra edge makes them even more attractive to employers.
Introduction to Data Science
Data Mining and Visualisation
Research Methods and Dissertation Preparation
Choose three of the following:
Information Systems Modelling
Information Systems in Organisations
Research Data Management
Researching Social Media
Lectures, including guest lectures from professional practitioners
Computer laboratory sessions