CS5264 Decision making technologies

Course description

The objective of this module is to introduce students to decision making technologies that can support decision making in the financial, operational, marketing and other strategic areas. Over the past two decades, increasing research efforts have been directed at finding new machine learning (ML) techniques for decision making and their possible application in solving practical problems. ML techniques such as artificial neural network methods have been proven to be powerful tools for business decision making. Among the application problems where ML techniques outperform traditional decision making methods such as statistical methods are credit rating, bankruptcy analysis, foreign exchange rate predictions and many others.

The techniques covered in this course include neural networks for classification/regression/clustering, genetic algorithm for optimization, decision tree methods, support vector machine and data mining. Journal articles that present new techniques for decision making and/or describe successful application of the existing methods in solving practical problems will be discussed in class.

Background assumed:

Calculus, matrix algebra and basic probability. Knowledge of optimization techniques such as linear programming and quadratic programming will be useful.