This programme is also available as a 240 credit routeway studied over two years. Students who choose this option will undertake a group design project and dissertation.
Data Science is an emerging discipline that aims to extract unique insights by extending the field of statistics to incorporate advances in computing, particularly in relation to large quantities of data.
It is estimated that 90% of the world's data was created in the last two years and that each day, over 2.5 billion gigabytes of data is created. Between 2012 and 2017 the take up of big data analytics amongst large enterprises in the UK more than doubled from 14% to 29%. The number of big data specialist staff working in large firms is predicted to increase by 243% to approximately 69,000 employees.
The challenges in data science are multi-faceted and very complex in their nature, including handling the huge amount of data in incompatible legacy databases. By exploiting cloud computing services, data scientists are now relatively free from the constraints of hardware and can concentrate on applying their domain knowledge and experience to make sense of the data. They can apply advanced statistical techniques and machine learning algorithms to make informed decisions which can deliver a major impact on their organisations. The programme comprises six core modules covering statistical and computing techniques plus an extended research project. It is designed to give you the knowledge to move into the world of work as a qualified Data Scientist or to carry out further research through a PhD or equivalent. It is delivered via a combination of lectures, tutorials and and hands-on computer laboratory sessions. A major component of the MSc programme is the research project module, which will give you the opportunity to work on a high-level original research topic, with guidance from an experienced researcher and supervisor.
The new 240 credit route includes a Group Design Project which aims to apply data science to the solution of a real-world problem. This will help to consolidate knowledge and skills learned during the first year, as well as develop new ones.
Why should I choose the 2 year route?
Your programme is made up of a number of core modules which are part of the course framework. Some programmes also have optional modules that can be selected to enhance your learning in certain areas and many feature a dissertation, extended report or research project to demonstrate your advanced learning.
See website for module information.
To cater for the wide-ranging content of our courses and the varied learning preferences of our students, we offer a range of assessment methods on each programme. Assessment techniques vary from module to module to reflect relevant assessment approaches and the key learning points of each topic.
You will be assessed via a combination of exams, coursework and an extended report based on your dissertation project. Typically 50% of your mark comes from coursework and 50% from an exam, although some modules may be assessed entirely by coursework done in the computer lab.
LJMU has an excellent employability record with 96% (HESA 2018) of our postgraduates in work or further study six months after graduation. Our applied learning techniques and strong industry connections ensure our students are fully prepared for the workplace on graduation and understand how to apply their knowledge in a real world context.
This programme is particularly focussed on preparing you for a career in industry or for PhD level study.
Data science is a growing area of demand with a predicted scarcity of expertise forecast over the next decade. LJMU has strong links with many graduate employers of data scientists who value the skills developed in the course such as accessing, manipulating and drawing insight from large volumes of complex data; assimilating information from the research literature and scientific and technical writing.
The programme enables you to plan and complete a substantial programme of original research at the highest level. We expect that many projects should have the potential to result in papers in refereed journals and serve as the starting point for PhD level work.
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