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
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
       Spec04  Mathematical Analytics
In addition to the above courses offered by the Mathematical Institute, students are strongly 
encouraged to consider electives from Statistics, Computer Science, and Engineering departments.
Each of these courses offer numerous courses in data science and a student interested in a career in data science should experience the views of this topic from multiple departments.