Subject code: MA5832:03
This subject will expose you to 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 sophisticated machine learning methods:
- Outlier detection
- Feature selection
Students who successfully complete this subject will be able to:
- 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.
Assessment for this course will occur at various times across the seven-week study period. Tasks may include online quizzes, discussion board activity, portfolio development, case studies, reflection, literature reviews presentations and reports.Feedback will be provided to you throughout the study period as well as a final grade at the conclusion of the study period.
Please note, unit structure and content are subject to change. Contact your JCU Online student advisor on 1300 535 919 for more information based on your particular circumstances.