University of Technology Sydney

32513 Advanced Data Analytics Algorithms

6cp; Forms of attendance and mode of delivery in this subject have changed to enable social distancing and reduce the risks of spreading COVID-19 in our community.
Requisite(s): (((32130 Fundamentals of Data Analytics OR 31250 Introduction to Data Analytics)) OR ((25776 Foundations of Business Analytics OR 26776 Foundations of Business Analytics) AND (42046 Data Processing Using R OR 42047 Data Processing Using Python OR 25777 Data Processing Using SAS)) OR 36106 Machine Learning Algorithms and Applications )
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Anti-requisite(s): 31005 Machine Learning
Recommended studies: knowledge of database technologies

Postgraduate

Description

Advanced data analytics address the problem of learning from data, which is an exciting field studying how intelligent agents can learn from and adapt to experience and how to realise such capacity on digital computers. It is applied in many fields of business, industry and science to discover new information and knowledge. This subject takes a machine learning-orientated approach. At the heart of machine learning are the knowledge discovery algorithms. This subject builds on previous data analytics subjects to give an understanding of how both basic and more powerful algorithms work. It consists of both hands-on practice and fundamental theories. Students learn important techniques in the field by implementation and theoretical analysis. The subject also introduces practical applications of machine learning, especially in the field of artificial intelligence.

Typical availability

Spring session, City campus


Detailed subject description.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.