Browse courses to find something that interests you.
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 microcredential will demonstrate analytics expertise and the professional communication of analytics.
This microcredential aligns with the 2 credit point subject, Applied Data Analytics (42823) 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 microcredential may qualify for recognition of prior learning at this and other institutions.
This microcredential is suitable for professionals from a wide range of sectors and backgrounds, who have completed our Data Analytics Foundations and Advanced Data Analytics microcredentials, or elsewise have professional experience in the field.
UTS microcredentials are developed for professionals with a capacity to undertake postgraduate tertiary education.
Full price: $1,595.00 (GST-free)*
*Price subject to change. Please check price at time of purchase.
During this course, you will meet and work with a dedicated course facilitator who will support your learning and engagement with teaching resources designed by the lead academic and team of experts from the Faculty of Engineering and IT.
The course is structured into five modules. Each module comprises self-study materials and facilitated online sessions. The five modules and key topics covered are:
Module 1 - Feature selection
Module 2 - Hyper-parameter optimisation
Module 3 - Knowledge discovery process
Module 4 - Research landscape in data analytics
Module 5 - Industrial applications
This course is delivered in a scheduled format over ten weeks.
Each week (during weeks 1 to 8) you will participate in an online session where you will have the chance to apply what you've learned, ask questions and hear from other participants who are taking the course with you. The workshops are led by the course facilitator.
Weeks nine and ten are planned to give you time to complete the final assignment, with support and scheduled Q&A sessions provided.
This course includes weekly, live, one-hour online tutorials and one-hour weekly Q&A sessions facilitated by an expert UTS academic supporting self-study and online learning activities.
Case studies of real-world business illustrate applications of data mining techniques. The workshop sessions focus on hands-on experience in data mining and data analytics tools and understanding and interpretation of the results.
Regular formative quizzes throughout the microcredential will allow participants to gauge their progress.
Upon successful completion of this course, you will be able to implement a data mining project in a business environment.
The graded assessment task is a data mining project using enterprise-specific or open-source data. The project is self-directed, with the support of the academic. It is an iterative process, including business understanding, data understanding, data preparation, modelling, evaluation and deployment.
A written report will be required to be submitted, describing the plan, approaches deployed, results and your reflection on the in-class oral feedback of the approach.
Length: 2,000 words
|Avg 5 hrs/wk|
Discover innovative approaches to assessment and evaluation to transform your learning design practice.
Learn expert-level field sampling skills, how to correctly interpret and apply water data and safety guidelines. [7 wks, avg 16 hrs/wk]
Learn how to identify plants and perform vegetation surveys to deliver highly informative biodiversity assessments. [7 wks, avg 14 hrs/wk]
Be a design thinker and discover creative, rigorous methods for developing new learning initiatives. [5 wks, avg 15 hrs/wk]
Enhance your knowledge of sustainability and its potential to create long-term value. [7wks, avg 10hrs/wk]