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Designed for data science practitioners, or as a follow-up to our Advanced Data Analytics micro-credential, this micro-credential focuses on the implementation and evaluation of the data mining and knowledge discovery process. Participants will be able to explore the current data analytics research landscape and focus on the deployment of results and industry applications.

About this micro-credential

Applied Data Analytics will develop the autonomy of participants to plan and implement a data mining project using the cross-industry standard process for data mining, known as CRISP-DM (the most common approach to data mining). From pre-processing, the deployment of results, representing patterns as rules, functions and cases, model deployment and industry applications, this practical, problem-based micro-credential will demonstrate analytics expertise and the professional communication of analytics.

Key benefits of this micro-credential

Learn to evaluate, implement and communicate professionally on best-practice and research-driven approaches to data analytics projects
Highly industry-focused; cover examples from a range of sectors, focusing on data-driven decision making
Complete as a self-contained course, or as a potential pathway to future postgraduate study.

Who should do this micro-credential?

This micro-credential is suitable for professionals from a wide range of sectors and backgrounds, who have completed our Data Analytics Foundations and Advanced Data Analytics micro-credentials, or elsewise have professional experience in the field.

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

Course learning objectives

Upon successful completion of this course, you will be able to implement a data mining project in a business environment.