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Course content

The course provides a professional and popular postgraduate programme of study that develops in students a critical appreciation of data science and the use of software to analyse and synthesise data.

Data Science or "Big Data" has never been more important. Modern computing systems and software have allowed greater insights to be garnered from very larger data sets and to provide actionable information. 

Graduates from this course will be equipped with the necessary skills and knowledge to develop and manage data science systems, thus enabling students to enhance their existing skills in anticipation of meeting the increasing commercial demand in this area.

Course Content

The following modules will be studied on the programme and are all compulsory to gain the MSc in Data Science:

  • Technology Project Management (20 credits)
  • Information Security and Document Management (20 credits)
  • Research Methods for Technology Dissertations (20 credits)
  • Technology Dissertation (40 credits)
  • Business Analysis (20 credits)
  • Social Computing (20 credits)
  • Geospatial Analysis (20 credits)
  • Programming for Data Analysis (20 credits)

There are three exit points from the degree: 

Postgraduate Certificate in Higher Education (PgCert) after successful completion of three modules.

Postgraduate Diploma in Higher Education (PgDip) awarded completion of 120 credits

The MSc is awarded on successful completion of all taught elements as well as submission of a 12,000 word dissertation project.

Learning & Teaching

Lectures

Lectures are a major part of the teaching strategy for the programme. Lectures are an effective way of delivering core material and establishing a framework for a module against which other material can be set.

Modular Subject Tutorials

Tutorials are meetings of a student or group of students with a lecturer or lecturers and are used in two ways within the programme:

  • expanding upon material covered in lectures through an enquiry-driven problem solving approach
  • remedial work to overcome any deficiencies in a student's background knowledge.

Seminars

Seminars involve a student or students presenting previously prepared work to peers and a lecturer. This strategy is used to extend specific theoretical or practical concepts as well as introducing problem solving exercises. Seminars are used in most modules and provide students with valuable experience in presentational skills as well as providing staff with a method of assessing student-centred learning.

Practical Workshops

In these classes students are able to practise and refine their skills in a supportive environment where they can receive feedback from a member of academic staff. Practical workshops represent a valuable transition between theory and the workplace.

Case Studies

Case studies are a teaching and learning strategy, employed in a range of modules; they also are a useful assessment tool. Students are presented with or asked to develop real or simulated complex problems which they are required to analyse in detail and then synthesise/present their own solution in writing or orally.

Moodle

All modules will be supported by Moodle and provide students with a wide range of learning material and study guidance. 

Assessment

Assessments take the form of examinations (seen/unseen, open book, essays/short answers), essays, practical assessments, presentations, role-plays, individual and group reports, and a dissertation or a developmental project.

Employability & Careers

Graduates will typically pursue careers as data analysts, IT consultants and managers in the business in addition to a range of posts involving the analysis of data. The programme also gives students a range of computing skills that could be applied to any role within the fields of business and computing.


Visit the Data Science - MSc/PgD/PgC page on the Cardiff Metropolitan University website for more details!

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