Faculty of Information Technology
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Monash Online offerings are only available to students enrolled in the Graduate Diploma in Data ScienceGraduate Diploma in Data Science (http://online.monash.edu/course/graduate-diploma-data-science/?Access_Code=MON-GDDS-SEO2&utm_source=seo2&utm_medium=referral&utm_campaign=MON-GDDS-SEO2) via Monash Online.
This unit aims to provide students with the necessary analytical and data modelling skills for the roles of a data scientist or business analyst. Students will be introduced to established and contemporary Machine Learning techniques for data analysis and presentation using widely available analysis software. They will look at a number of characteristic problems/data sets and analyse them with appropriate machine learning and statistical algorithms implemented in software including R, Python and RapidMiner. Those algorithms include regression, classification, clustering and so on, and the focus is on understanding the problems, models, and use of software, but not in the underlying theory. They will need to interpret the results and the suitability of the algorithms.
On successful completion of this unit, students should be able to:
In-semester assessment: 100%
Minimum total expected workload equals 144 hours per semester comprising:
(a.) Contact hours for on-campus students:
(b.) Contact hours for Monash Online students:
(c.) Additional requirements (all students):
See also Unit timetable information
Advanced data analytics