Courses

Machine learning and data science makes use of and highlights new challenges throughout mathematics. Some of the most prevalent notions used in data science are algorithms, modelling and probability. Students interested in data science will benefit from the general prelims curriculum, with the Trinity term course “Statistics and Data Analysis” the first offering specifically in data science. Part A students wishing to pursue data science are strongly encouraged to take A8 Probability and A7 Numerical Analysis.

Additional courses aligned with data science include:

Part B:

MT   B6.3 Integer Programming
         B8.1 Probability, Measure and Martingales
         B8.4 Information Theory
         B8.5 Graph Theory
 
HT   B5.1 Stochastic Modelling of Biological Processes
         B8.2 Continuous Martingales and Stochastic Calculus
         B8.3 Mathematical Models of Financial Derivatives
         B8.6 High Dimensional Probability
  
Part C:

MT  C6.1 Numerical Linear Algebra
        C8.1 Stochastic Differential Equations
        C8.3 Combinatorics
 
HT   C3.9 Computational Algebraic Topology
        C5.4  Networks
        C5.10 Mathematics and Data Science for Development
        C6.2  Continuous Optimisation
        C6.5  Theories of Deep Learning
        C8.2  Stochastic Analysis and PDEs
        C8.4  Probabilistic Combinatorics
        C8.7  Optimal Control 
        Spec04  Mathematical Analytics
 
In addition to the above courses offered by the Mathematical Institute, students are strongly 
encouraged to consider electives from Statistics and  Computer Science which are listed at:

https://courses.maths.ox.ac.uk/node/42899