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 core 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).
- Applied Machine Learning (COMP0081) (15 credits)
- Introduction to Machine Learning (COMP0088) (15 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)
- Introduction to Deep Learning (COMP0090) (15 credits)
- Machine Vision (COMP0137) (15 credits)
- Multi-agent Artificial Intellgience (COMP0124) (15 credits)
- Reinforcement Learning (COMP0089) (15 credits)
- Statistical Natural Language Processing (COMP0087) (15 credits)
Students must choose 30 to 45 credits of elective modules.
- Affective Computing and Human-Robot Interaction (COMP0053) (15 credits)
- Applied Bayesian Methods (STAT0031) (15 credits)
- Bioinformatics (COMP0082) (15 credits)
- Computational Modelling for Biomedical Imaging (COMP0118) (15 credits)
- Decision and Risk (STAT0011) (15 credits)
- Forecasting (STAT0010) (15 credits)
- Graphical Models (COMP0080) (15 credits)
- Robot Vision and Navigation (COMP0130) (15 credits)
- Robotic Systems Engineering (COMP0127) (15 credits)
- Statistical Design of Investigations (STAT0029) (15 credits)
- Supervised Learning (COMP0078) (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 whic culminates in a dissertation of 10,000-12,000 words.