Data Science brings together computational and statistical skills for data-driven problem solving. This rapidly expanding area includes machine learning, deep learning, large-scale data analysis and has applications in e-commerce, search/information retrieval, natural language modelling, finance, bioinformatics and related areas in artificial intelligence.
The programme comprises core machine learning methodology and an introduction to statistical science, combined with a set of more specialised and advanced options covering computing and statistical modelling. Projects are offered both within UCL Computer Science and from a wide range of industry partners.
Students undertake modules to the value of 180 credits.
The programme consists of three compulsory modules (45 credits), five optional modules (75credits) and a dissertation/report (60 credits).
Core modules -Applied Machine Learning -Introduction to Supervised Learning -Introduction to Statistical Data Science
Optional modules - students choose a minimum of 30 credits and a maximum of 60 credits from the following optional modules: -Cloud Computing (Birkbeck) -Machine Vision -Information Retrieval & Data Mining -Statistical Natural Language Processing -Web Economics
Students choose a minimum of 0 credits and a maximum of 30 credits from these optional Statistics modules: -Statistical Design of Investigations -Applied Bayesian Methods -Decision & Risk
Students choose a minimum of 15 credits and a maximum of 15 credits from these elective modules: -Supervised Learning -Graphical Models -Bioinformatics -Affective Computing and Human-Robot Interaction -Computational Modelling for Biomedical Imaging -Stochastic Systems -Forecasting
Dissertation/report All students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words.
Teaching and learning The programme is delivered though a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed through a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.
Data science professionals are increasingly sought after as the integration of statistical and computational analytical tools becomes more essential to organisations. A thorough understanding of the fundamentals required from the best practitioners, and this programme's broad base, assists data scientists to adapt to rapidly evolving goals. This is a new degree and information on graduate destinations is not currently available. However, MSc graduates from across the department frequently find roles with major tech and finance companies including: -Google Deepmind -Microsoft Research -Dunnhumby -Index Ventures -Last.fm -Cisco -Deutsche Bank -IBM -Morgan Stanley
Why study this degree at UCL?
The 2014 Research Excellence Framework ranked UCL first in the UK for computer science. 61% of its research work is rated as world-leading and 96% as internationally excellent.
UCL Computer Science staff have research interests ranging from foundational machine learning and large-scale data analysis to commercial aspect of business intelligence. Our extensive links to companies provide students with opportunities to carry out the research project with an industry partner.
The department also enjoys strong collaborative relationships across UCL; and exposure to interdisciplinary research spanning UCL Computer Science and UCl Statistical Science will provide students with a broad perspective of the field. UCL is home to regular machine learning masterclasses and big data seminars.
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 Bachelor's degree in a quantitative discipline (such as mathematics, computer science, engineering, physics or statistics) from a UK university or an overseas, qualification of an equivalent standard. Knowledge of mathematical methods including linear algebra and calculus at first-year university level is required. Depending on the modules selected, students undertake assignments that contain programming elements and prior experience in a high-level programming language (R/matlab/python) is useful. Relevant professional experience will also be taken into consideration.
Recipient: University College London
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