Data Science Theory (ECON0125)

Description

This module aims to provide a rigorous treatment of data science methods, ranging from classical statistical methods to modern machine learning methods. The module provides a detailed mathematical explanation of a number of methods, including supervised and unsupervised learning techniques such as linear regression, logistic regression, additive models, neural networks, random forests, and ensemble learning.