Machine Learning MSc is a unique programme that introduces students to the computational, mathematical and business views of machine learning
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 one core module (15 credits), two to seven optional modules (30 to 105 credits), up to five elective modules (0 to 75 credits), and a research project (60 credits).
- Supervised Learning (COMP0078) (15 credits)
Students must select a minimum of 30 credits and a maximum of 105 credits from these optional modules, which must include either Graphical Models (COMP0080) or Probabilistic and Unsupervised Learning (COMP0086).
- Advanced Topics in Machine Learning (COMP0083) (15 credits)
- Applied Machine Learning (COMP0081) (15 credits)
- Approximate Inference and Learning in Probabilistic Models (COMP0085) (15 credits)
- Bayesian Deep Learning (COMP0171) (15 credits)
- Graphical Models (COMP0080) (15 credits)
- Introduction to Deep Learning (COMP0090) (15 credits)
- Machine Learning Seminar (COMP0168) (15 credits)
- Machine Vision (COMP0137) (15 credits)
- Probabilistic and Unsupervised Learning (COMP0086) (15 credits)
- Reinforcement Learning (COMP0089) (15 credits)
- Statistical Learning Theory (COMP0175) (15 credits)
- Statistical Natural Language Processing (COMP0087) (15 credits)
Students select a minimum of 0 credits and a maximum of 75 credits from these elective modules.
- Affective Computing and Human-Robot Interaction (COMP0053) (15 credits)
- AI for Biomedicine and Healthcare (COMP0172) (15 credits)
- AI for Sustainable Development (COMP0173) (15 credits)
- Bioinformatics (COMP0082) (15 credits)
- Computational Modelling for Biomedical Imaging (COMP0118) (15 credits)
- Information Retrieval and Data Mining (COMP0084) (15 credits)
- Inverse Problems in Imaging (COMP0114) (15 credits)
- Numerical Optimisation (COMP0120) (15 credits)
- Robot Vision and Navigation (COMP0130) (15 credits)
- Robotic Control Theory and Systems (COMP0128) (15 credits)
- Robotic Systems Engineering (COMP0127) (15 credits)
Please note: the availability and delivery of optional modules may vary, depending on your selection.
Students undertake an independent or team-based research project worth 60 credits. The project will be related to a problem of industrial interest or a topic near the leading edge of research, and culminates in a dissertation.
- MSc Machine Learning Project (COMP0091) (60 credits)