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Overview

Increasingly, organisations need to analyse enormous data sets to determine useful structure in them. In response to this, a range of statistical methods and tools have been developed in recent times to allow accurate and quick analysis of these sets. Machine learning is the algorithmic approach to learning from data. … For more content click the Read More button below. Topics include: decision tree algorithms, regression and model tree algorithms, neural network learning, support vector machines, rule learning (such as association rules), lazy learning, version spaces, evaluating the performance of machine learning algorithms, Bayesian learning and model selection, algorithm-independent learning, ensemble learning, kernel methods, unsupervised learning (such as clustering) and inductive logic programming (relational learning).

Conditions for Enrolment

Prerequisite: ZZEN9021 and enrolment in either the 5646 or 8646 Data Science program.

Delivery

Fully online - Intensive

Fees

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)