Machine Learning & AI for Business

Machine Learning is an integral tool in a business analyst’s arsenal and plays a critical role in predicting a range of outcomes, including consumer behaviour, future performance and other organisational outcomes of interest. In real‐time, data collection and data wrangling are the important steps in deploying machine learning models. This subject covers the application of a range of supervised and unsupervised learning techniques from machine learning in a range of semi‐ or non‐structured decision problems in a data rich environment including senior team decision support, decision optimisation across firm boundaries (e.g., supply change and supplier coordination), customer facing algorithms to support product selection and other decisions. The techniques covered will include decision trees, regression trees, neural networks and clustering methods. Ethical concerns associated with the analysis of business problems using the methods taught in the subject will also be integrated into the subject.

应用机器学习和AI解决商业问题。

• 1Understand the fundamentals of AI and ML and their applications in business contexts;
• 2Apply basic programming skills in Python and utilise data libraries to generate business solutions through AI and ML;
• 3Application of supervised learning algorithms including decision trees and regression trees to business problems.;
• 4Application of unsupervised learning algorithms such as association rules and clustering methods, to business problems;
• 5Application of neural network models and deep learning in marketing in business predictive modelling; and
• 6Understanding the ethical concerns, such as AI bias, in using AI/ML in business and how to mitigate these concerns.