Web Science and Big Data Analytics MRes

Students will gain a detailed knowledge and understanding of the fundamental principles and technological components of the World Wide Web, learning not only the latest web search and information retrieval technologies and their underlying computational and statistical methods, but also studying essential large-scale data analytics to extract insights and patterns from vast amounts of unstructured data.

Students undertake modules to the value of 180 credits.

The programme consists of two core modules (30 credits), either four optional modules (60 credits) or three optional and one elective module, and the research dissertation (90 credits).

• Investigating Research (15 credits)
• Researcher Professional Development (15 credits)

Students must choose a minimum of 45 and a maximum of 60 credits of optional modules. Students may also choose up to 15 credits from electives.

• Affective Computing and Human-Robot Interaction (15 credits)
• Complex Networks and Web (15 credits)
• Computer Graphics (15 credits)
• Graphical Models (15 credits)
• Information Retrieval and Data Mining (15 credits)
• Machine Vision (15 credits)
• Probabilistic and Unsupervised Learning (15 credits)
• Statistical Natural Language Processing (15 credits)
• Web Economics (15 credits)

Dissertation/report

All students undertake an independent research project which culminates in a substantial dissertation.

The programme is delivered through a combination of lectures, tutorials and seminars. Lectures are often supported by laboratory work with help from demonstrators. For the research project, each student liaises with their academic or industrial supervisor to choose a study area of mutual interest. Student performance is assessed by unseen written examinations, coursework and the research dissertation.