MSc course on Learning from Data

The information revolution is leading to unprecedented volumes of stored data, representing a gold mine of useful information with the potential to impact on many fields such medicine, finance, and scientific research. The Learning from Data specialism provides a comprehensive grounding in key techniques such as machine learning, probabilistic inference, pattern recognition and neural networks, and will leave students well placed for postgraduate research towards a PhD or for industrial employment.

Some interesting applications of such methods are:

• Detecting satellite tracks and linear artefacts in astronomical images
• Tracking people against cluttered backgrounds
• Separating multiple audio tracks (blind source separation)
• Predicting burglaries with Bayesian networks
• Learning about multiple objects from images
• Analyzing DNA microarray gene expression data
• Segmenting aerial images

Astronomical artefact  detection	Microarray data  analysis	Car start  belief network

Further details on these applications can be found here.
 

Students who are primarily interested in Learning from Data can choose to specialise just in this area. The Learning from Data specialism comprises eight taught modules, plus a five month long research project. Of the eight modules, there are three compulsory inner core modules: Learning from Data 1, Probabilistic Modelling and Reasoning, Data Mining and Exploration. Students must also take two modules from Learning from Data 2, Genetic Algorithms and Genetic Programming, Visualization, Applied Databases, Data Intensive Linguistics. The remaining modules can be chosen from the whole range of MSc modules, although we would normally expect one of them to be a progamming module appropriate to the student's prior programming experience. Further details on the modules can be obtained from the webpage for current MSc students.

We have a number of EPsrc grants available to support UK students who have a very good honours degree (or equivalent qualification) in a numerate area such as Computer Science, Physics etc. (Partial support may be available for EU students.) Please indicate on your application form if you wish to be considered for this course, which would lead to an MSc in Informatics degree.