The course is split equally in two between mathematics and computer science. The intended goal of this degree is to develop mathematical problem
solving skills with the technical knowledge of software to be better able to solve a variety of issues in any field requiring
computational, analytical or rigorous logical thinking.
My reason for choosing this degree specifically is in large part due to
its malleability with regards to future career choices but also my growing interest in the use of large data sets to predict,
discover and also create new inventions and knowledge. Below are a list of optional modules I plan on taking as my degree progresses although
the ones shown are subject to change.
PS: Year 4 is a placement year hence there aren't any modules available
Year 2
The Basics
Data Structures and Algorithms
Fundamentals of Machine learning
Year 3
Getting hot with Mathematics
Computer Algebra
Differential and Geometric Analysis
Optimisation Methods of Operational Research
Cryptography
Numberical Optimisation of large-scale systems
Intelligent Control and Cognitive Systems
Year 5 S1
Trying to make things Intelligent
Intelligent Agents
Machine Learning
Statistics for Data Science
Number Theory
Year 5 S2
The Cherries on top
Scientific Computing
Theory of Partial Differential Equations
Projective Geomtetry
Collaborative Systems