Teaching team
- Jeremie Clos
- Lucas Fonseca
Core ideas of the module
An opinionated introduction to the core challenges of data science and machine learning.
Our goal for this module is to enable you to appreciate the range of data analysis problems that can be modelled computationally and a range of techniques that are suitable to analyse and solve those problems. Topics covered include: basic statistics; types of data; data visualisation techniques; data modelling; data pre-processing methods including data imputation; forecasting methods; clustering and classification methods ; data simulation and model interpretation techniques to aid decision support. This is a level 4 module aimed at both MSc students and year 3/4 undergraduate students, and it is generally open at non-CS students. For this reason, it has a relatively low barrier of entry and requires quite a bit of work to get everyone to a similar level during the term.
[UNDER CONSTRUCTION]