The MRes covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and makes them well equipped to proceed to become the ideal choice for the best employers in internet-related industries and the areas requiring big data analytical skills.
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), four option modules (60 credits), and the research dissertation (90 credits).
Core modules -Investigating Research -Researcher Professional Development
Optional modules -Complex Networks and Web -Web Economics -Information Retrieval and Data Mining -Distributed Systems and Security -Multimedia Systems -Or an elective module from other Computer Science programmes
Dissertation/report All students undertake an independent research project which culminates in a substantial dissertation.
Teaching and learning 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 is liaised 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.
Graduates from UCL are keenly sought by the world's leading organisations, and many progress in their careers to secure senior and influential positions. Graduates of our Web Science and Big Data Analytics programmes are expected to develop careers in scientific research, the internet-based industry and other professional areas that require big data analytics skills.
Employability The skill set obtained from our MRes makes our students the ideal choice for the best employers in internet-related industries and sectors requiring big data analytics. The MRes has a unique industry connection as almost all our lecturers have industry experience. Through long-term collaborations with big players in the field such as Google, Microsoft and BT, their research is driven by the fundamental technical challenges faced by the industry. Throughout the degree, our students have the chance to interact with our industry collaborators and previous students, and have placement opportunities to address specific technical problems faced by the industry.
Why study this degree at UCL?
UCL Computer Science is recognised as a world leader in teaching and research, and was one of the top-rated departments in the country according to the UK government's recent Research Excellence Framework.
Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries, from entertainment to finance.
We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.
Selection criteria: The bursary will be awarded based on financial need only as determined by the Student Funding Office.Value, Benefits and Duration: - The value of the bursary is £15,000. The payment is to be applied to tuition fees in the first instance, with any remainder being paid to the successful applicant towards maintenance in termly instalments. - The bursary is tenable for one year only. - The bursary may not be held alongside other tuition fee only awards.
Value of Scholarship(s)
Applicants must be: - prospective full-time UK Master's students who are undertaking a one-year programme of study in the Faculties of the Built Environment, Engineering Sciences or Mathematical & Physical Sciences (BEAMS) in 2015/16 - currently holding a first-class Bachelor's degree; and - in financial need.
A minimum of an upper second-class UK Bachelor's degree in a highly quantitative subject, or an overseas qualification of an equivalent standard. Students should also have some experience with a programming language such as Java or python.
Recipient: University College London
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