Master of Science - MS240

Postgraduate Diploma - PD

Master of Science - MS

Level 7 Core

Level 7 Optional

Level 7

Programme Structure

Undergraduate honours degree (2:2 or better) in a numerate, scientific or computer based subject. Plus A level or equivalent in Mathematics at Grade C or above. Individual cases will be considered on their merit. LJMU welcomes applications from international students. In addition to normal entry requirements, you will be expected to demonstrate a very good level of English language competence, for example an IELTS score of 6.5 or equivalent with a minimum of 6.0 in each component or the award of a degree within the last two years from a recognized UK higher education provider.

Undergraduate honours degree (2:2 or better) in a numerate, scientific or computer based subject. Plus A level or equivalent in Mathematics at Grade C or above. Individual cases will be considered on their merit. LJMU welcomes applications from international students. In addition to normal entry requirements, you will be expected to demonstrate a very good level of English language competence, for example an IELTS score of 6.5 or equivalent with a minimum of 6.0 in each component or the award of a degree within the last two years from a recognized UK higher education provider. Offerings: All

Analyse and solve set problems, choosing the appropriate techniques and technologies.

Demonstrate the application of statistical, machine learning and data visualisation techniques to familiar and unfamiliar problems in data science.

Critically review research literature and communicate with peers.

Break down complex problems into a logically structured set of achievable tasks, for work alone or as part of a team.

Demonstrate the application of big data computing technologies and techniques.

Communicate effectively, both written and verbally, to expert and diverse audiences.

Apply planning, research methodology and analytical skills to an in-depth study of a chosen research area

Demonstrate a thorough knowledge of the statistical techniques used in data science.

Show originality in the application of knowledge, together with a practical understanding of the critical evaluation of research, scholarship and methodologies within data science.

Demonstrate a clear understanding of the legal, ethical and data protection issues in data science.

Demonstrate practical experience of the solution of problems in data science using modern computational languages and techniques.

Critically evaluate information from a variety of sources, and draw and defend conclusions

Course Catalogue

Data Science - 35895 - MSc