Year 1 Semester 1

Statistical Modelling Concepts for Data Science builds the statistical reasoning that sound data science depends on: probability and distributions, simulation and the Central Limit Theorem, estimation and hypothesis testing, linear regression and its diagnostics, logistic and other generalised linear models, time series forecasting, resampling and regularisation. You learn by doing, with Python labs, discussion forums and a personalised data analysis project that runs on your own computer.