BUS265 - Machine Learning and Digital Technology - 2023/24

This module provides an introduction to the main concepts and techniques of machine learning and digital technology relevant to management research and international business. Students will learn how to use tools and techniques from machine learning, artificial intelligence, and natural language processing (including Large Language Models (LLMs)) to solve business case problems and improve decision-making. The module will introduce students to the most important machine learning algorithms used in business research for supervised and unsupervised learning. A variety of real-world datasets are used, including tabular, text, and network data. Applications include the prediction of Airbnb apartment prices, exploration of COVID-19 human mobility patterns, clustering of movie ratings data, prediction of vaccination hesitancy, text analysis of review data, community detection of network data, and evaluation of criminal risk assessment algorithms. Emphasis will be placed on the use of Python programming language, with practical examples, real-world data, hands-on coding, and interpretation of results. Prior knowledge of programming is not required as coding for data analysis will be taught from first principles. The module focuses on developing good research practices and reproducible machine learning workflows. Issues of ethics, bias, and fairness of machine learning technologies are examined throughout the module.