Data Science MSc

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules in computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research dissertation/report (60 credits).

• Introduction to Statistical Data Science
• Introduction to Machine Learning
• Statistical Design of Investigations
• Statistical Computing

• Applied Bayesian Methods
• Decision & Risk
• Factorial Experimentation
• Forecasting
• Quantitative Modelling of Operational Risk and Insurance Analytics
• Selected Topics in Statistics
• Stochastic Methods in Finance I
• Stochastic Methods in Finance II
• Stochastic Systems

• Affective Computing and Human-Robot Interaction
• Graphical Models
• Statistical Natural Language Processing
• Information Retrieval & Data Mining

All students undertake an independent research project, culminating in a dissertation usually of 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.