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MS4424 - Advanced Predictive Analytics

Offering Academic Unit
Department of Management Sciences
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
Pre-cursor(s)
Course Offering Term*:
Not offering in current academic year

* The offering term is subject to change without prior notice
 
Course Aims


Data mining plays a very important role in business – sales, marketing, and customer support. It is being used to discover implicit and useful knowledge from vast datasets. The course covers concepts fundamental to the understanding and applications of advanced data mining methods to business problems.

In recent years, there is an explosive growth of data mining techniques, applications and computer capabilities. This course focuses on advanced data mining techniques and applications utilizing computing software such as R, Python or SAS. It is an extension of MS4224 Enterprise Data Mining and MS4252 Big Data Analytics covering data mining techniques used in predictive analytics. According to SAS Institute (the leader in business analytics software and services, and the largest independent vendor in the business intelligence market.), predictive analytics is “the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.” (https://www.sas.com/en_hk/insights/analytics/predictive-analytics.html). It is thought that the topics of this course together with the topics of other courses in the Business Analysis major provide students a comprehensive training in business analysis, and give them a competitive edge.

This course is different from MS4212 Predictive Analytics and Forecasting in that it analyses more granular data without a natural temporal ordering whereas MS4212 analyses time series data with a natural temporal ordering. Students are expected to have some programming language knowledge which is either learned from pre-cursor courses or by themselves.


Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 60%
Examination: 40%
Examination Duration: 3 hours
 
Detailed Course Information

MS4424.pdf