Course Catalogue

Data science is an emerging discipline that extends the field of statistics to incorporate advances in computing, especially with large quantities of data. It is a growing area of demand at both undergraduate and postgraduate level, with a predicted scarcity of expertise forecast over the next decade. There is a need for a level 7 programme to serve as a specialisation and conversion course aimed at numerate graduates aiming for industrial and academic positions in the Data Science marketplace. The MSc is founded on a strong foundation at LJMU of research activity in data analysis and big data computation. The aim of the programme is therefore to provide training in the skills and techniques of modern data science and give the student the ability to apply those skills and techniques fashion to create solutions to research and business problems. The students will gain an understanding not just of how to apply the techniques and skills, but also their limitations and how to synthesise their combination to gain greater insights.

The methods used to enable outcomes to be achieved and demonstrated are as follows: Acquisition of 1 - 13 is through a combination of lectures, tutorials, practical sessions and laboratory work. Throughout the learner is encouraged to undertake independent reading both to supplement and consolidate what is being taught / learnt and to broaden their individual knowledge and understanding of the subject. Knowledge and understanding (Skills 1-7 and 18-19) is assessed via formal examination, individual and team coursework, demonstration of practical work, and a full-scale individual MSc Dissertation. Skills 1 - 8 are taught through lectures and developed through tutorial work throughout the programme. Cognitive skills (Skills 1-2 and 11-16) are partly assessed via formal examinations, but mainly through coursework assessment. The MSc Dissertation allows a student to demonstrate his/her cognitive skills. Practical advanced skills (Skills 9-19) are developed throughout the programme. Specialist software such as virtual machines and private-cloud systems are available in department-maintained labs or remotely from specified PCs in the libraries. Key skills are developed throughout the programme in a variety of forms. Specifically through a combination of research related coursework, guided independent study and projects, examinations, group work and presentations. Key skills are assessed as part of coursework, projects, written examinations and presentations.

There are no external placements during the programme. However business skills of project development, management, implementation and presentation are embedded throughout the course. As part of the Research Methods (7637UPGRAD) module the students will have developed a business case/research proposal and project management plan which they will have “pitched” both in oral and written form. The subsequent research project (7611UPGRAD) can be viewed as a placement within an academic department to carry out research. Each student will be allocated to a team of two supervisors (main and second) who will act as their line-managers for the project. The supervisors will have complementary skill sets in the problem domain and the data science domain. Weekly 1 hour meetings of the supervisors and student will monitor progress and provide opportunities for developmental feedback. The aim is to run the projects in the same fashion as either an academic or industrial project is done externally. As part of the research methods and project modules, the students will be encouraged and assisted to develop a professional on-line presence.