The MathSys MSc year is structured to provide students with the training to tackle key challenges facing science, business and society.
It is dedicated to developing a broad portfolio of mathematical techniques through taught modules covering subjects such as Networks and Random Processes, Applied Dynamical Systems, Numerical Methods, Statistical Mechanics, Statistical Inference and Modern Topics in Mathematics Modelling. Alongside this, MSc students will also undertake projects and work on research problems that will have a strong emphasis on applied questions and practical approaches, and will be linked to real-world problems and experiences from our external collaborative partners.
Term 1 taught core modules
These modules run in term 1, 5 weeks each with two in parallel.
- MA933 Networks and random processes (12 CATS)
- MA930 Data Analysis (12 CATS)
- MA998 Applied dynamical systems (12 CATS)
- MA934 Numerical methods (12 CATS)
Other core modules
- MA932 MSc Study Groups (36 CATS), begins in term 2 and runs mainly in Easter vacation and term 3
- MA931 MSc Project (48 CATS), runs from mid June to September
Other compulsory activities
- MSc student meetings (usually Wednesdays 10-11) with administrator and MSc coordinator to discuss general questions (e.g. module registrations etc)
- Computational Techniques (term 1 Wednesdays 11-12)
- Complexity/MathSys Forum (usually Wednesdays 1-2): seminar series of the centre preceded by a joint sandwich lunch prepared by MSc students in groups
- Transferable skills activities
Taught optional modules
Most of these modules run in term 2, please check up to date timetables with individual departments. You should take at least 3 options summing to at least 48 CATS.
CS342 - 15 Machine Learning (in term 1 this year)
ST343 - 15 Topics in Data Science
CS409 - 15 Algorithmic Game Theory
CS904 -15 Computational Biology
CS909 - 15 Data Mining
CY903 - 12 Practical algorithms and data structures (apparently not running this year)
IM903 - Complexity in the Social Sciences (runs as a one week module after the end of term 2, you normally have to register for the 15 Cats version)
IM931 - Interdisciplinary Approaches to Machine Learning
MA999-15/18 Topics in Mathematical Modelling: From Equilibrium to Extreme Events and Life
MA4E7-15 Population Dynamics: Ecology and Epidemiology
MA5Q3-18 Topics in Complexity Science: Stellarator Mathematics
You can also choose other Masters level modules subject to approval of the course director as unusual options, a list of examples can be found here.