Data Science and Machine Learning MSc brings together computational and statistical skills for data-driven problem solving
To find out core information about this degree, such as entry requirements, programme length and cost, visit the UCL prospectus site.
Students undertake modules to the value of 180 credits.The programme consists of three compulsory modules (45 credits), two to three optional modules (30 to 45 credits), two to three elective modules (30 to 45 credits) and a dissertation (60 credits).
- Introduction to Machine Learning (COMP0088) (15 credits)
- Applied Machine Learning (COMP0081) (15 credits)
- MSc Machine Learning Project (COMP0091) (60 credits)
- Introduction to Statistical Data Science (STAT0032) (15 credits)
Students must choose 30 to 45 credits of optional modules.
- Information Retrieval and Data Mining (COMP0084) (15 credits)
- Statistical Natural Language Processing (COMP0087) (15 credits)
- Reinforcement Learning (COMP0089) (15 credits)
- Introduction to Deep Learning (COMP0090) (15 credits)
- Multi-agent Artificial Intellgience (COMP0124) (15 credits)
- Machine Vision (COMP0137) (15 credits)
Students must choose 30 to 45 credits of elective modules.
- Affective Computing and Human-Robot Interaction (COMP0053) (15 credits)
- Supervised Learning (COMP0078) (15 credits)
- Graphical Models (COMP0080) (15 credits)
- Bioinformatics (COMP0082) (15 credits)
- Computational Modelling for Biomedical Imaging (COMP0118) (15 credits)
- Robotic Systems Engineering (COMP0127) (15 credits)
- Robot Vision and Navigation (COMP0130) (15 credits)
- Forecasting (STAT0010) (15 credits)
- Decision and Risk (STAT0011) (15 credits)
- Statistical Design of Investigations (STAT0029) (15 credits)
- Applied Bayesian Methods (STAT0031) (15 credits)
Please note: the availability and delivery of modules may vary, based on your selected options as all choices are subject to timetabling constraints
All students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words.