JCU Australia logo

Subject Search

MA5832 - Data Mining and Machine Learning

Credit points: 3
Year: 2019
Student Contribution Band: Band 2
Administered by: College of Science and Engineering

This subject will provide students with a range of algorithms based on machine learning techniques for advanced data analysis and mining. These algorithms and techniques fall within the most common machine learning paradigms, namely, unsupervised, semi-supervised, and supervised learning. In particular, students will learn sophisticate machine learning methods for clustering, outlier detection, classification, feature selection, and regression.

Learning Outcomes

  • explain what machine learning for data mining is about and identify the most common tasks and roles of machine learning in the realm of data mining;
  • describe, choose, and apply unsupervised machine learning methods for descriptive data mining tasks, such as clustering and outlier detection;
  • describe, choose, and apply supervised techniques for dimensionality reduction via feature selection;
  • describe, choose, and apply semi-supervised and/or supervised machine learning methods for predictive data mining tasks, such as pattern classification and regression.
Prerequisites: MA5810 AND 24CP OF POSTGRADUATE SUBJECTS

Availabilities

JCU Online, External, Study Period 85
Census Date 12-Sep-2019
Coordinator: Professor Ronald White
Lecturers: Dr Dmitry Konovalov, Dr Carla Ewels, Dr Neil Fraser, Dr Sourav Das, Dr Kelly Trinh.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 65 hours - Online resources including readings, screencasts, embedded quizzing
  • assessment and self-directed study
Method of Delivery: Online - JCU
Assessment: quizzes or tests (20%); assignments (60%); computational laboratories/log book (20%).

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.