|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.
|Prerequisites:||MA5810 AND 24CP OF POSTGRADUATE SUBJECTS|
|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.|
The student workload for this 3 credit point subject is approximately 130 hours.
|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.