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Designed for professionals with some familiarity working with data, this micro-credential combines state-of-the-art research and practical techniques in data analytics, covering the knowledge and capacity to initiate and conduct data mining research and development projects.

About this micro-credential

Advanced Data Analytics develops skills in data classification and prediction through practical activities in decision tree induction, classification by support vector machine, ensemble methods and random forest, classification accuracy and identifying issues in prediction.

Building from the Data Analytics Foundations micro-credential, this course enables an exploratory data visualisation and evaluation of results.

Key benefits of this micro-credential

Build on your foundational data analytics skills without focusing on heavy maths or coding – this course uses a visual open-source platform (KNIME) to demonstrate and practice key concepts and models for participants without a programming background.
Learn to evaluate and choose between key machine learning methods and models through practical exercises.
Complete as a self-contained course, or as a potential pathway to future postgraduate study.

This micro-credential aligns with the 2 credit point subject, Advanced Data Analytics (42822) in the Graduate Certificate in Professional Practice (C11298), Graduate Diploma of Professional Practice (C06136), Master of Professional Practice (C04404), Graduate Certificate in Technology (C11301), Graduate Diploma in Technology (C06137) and Master of Technology (C04406).

This micro-credential may qualify for recognition of prior learning at this and other institutions.

Who should do this micro-credential?

This micro-credential is accessible to participants with some background in data or those who have completed the Data Analytics Foundations micro-credential.

UTS micro-credentials are developed for professionals with a capacity to undertake postgraduate tertiary education.

Course learning objectives

Upon successful completion of this micro-credential you will be able to apply data mining, pattern discovery, and analysis skills in predictive analytics of data sets.

You will be able to select an appropriate classifier or approach for a predictive analytics task and explain your approach and results to a peer.