This page lists approved microcredentials and other short courses. Where a microcredential has an approved credit arrangement, it is noted below.
Microcredential with approved credit arrangements
Credit-bearing microcredentials are assessed short programs of study that may be stacked and offer credit arrangements towards specific UOW award courses.
- Big Data Analytics with Application
- Infrastructure System of Systems Engineering
- Introduction to the Internet of Things
- Advanced Computational Methods with Applications in Logistics
- Urban Transport Planning for Digital Age
- Introduction to Agent-Based Modelling of Urban Systems
- Introduction to MBSE and SysML
- AWS Academy Cloud Foundation (Amazon)
- Principles and Practice for Difficult Venous Access
- Gerontological Nursing Competencies (GNCs)
Course overview
This introductory course on data science covers the following topics: data manipulation, data analysis with statistic and machine learning, data visualisation and how to work with large data sets. These concepts will be illustrated using programming languages often used and freely available, namely R, Python and SQL. The course presents in a practical way multivariate statistical analysis methods such as Regression, Clustering, Principal Component Analysis, Factor Analysis and ANOVA.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
Basic knowledge of linear algebra and programming experience is required.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
Infrastructure systems are socio-technical systems within an organisational environment. The presence of social and organisational aspects increases complexity and influences these systems throughout their life cycle, from conception and planning, engineering, operation, upgrades and final disposal. Infrastructure systems will be examined as ‘System of Systems’ (SoS). Various approaches for System of Systems Engineering (SoSE) will be presented and discussed. ‘Systems Thinking’, considered the most adequate approach to deal with the complexity of socio-technical SoS, will be presented and illustrated with practical examples. Designing for Adaptability and evolution in System of Systems Engineering (DANSE) methodology will be introduced. The course will address the fundamentals of modelling and simulation considered to be of great importance for Infrastructure SoSE.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
There are no pre-requisites for this course.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
The Internet of Things (IoT) is radically changing the technological landscapes. Applications opportunities are endless: home automation, healthcare, predictive maintenance, agriculture, energy management, or transportation are only some of those use cases. However, the IoT is more than just sensors, it’s a process ranging from remote data collection to data analytics in order to grasp the full potential of your data. This introductory course offers an introduction to the IoT covering not only the theoretical background and current usages, but also providing practical knowledge through hands-on tutorials and workshops. Students will gain expertise on the whole IoT process.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
Basic knowledge of Computer Science and Python is preferred but not required. Prior to the course, each student will have access to Code Combat to get familiar with Python.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
Today’s world is producing an ever increasing amount of data. Businesses then need data analysis to provide forward guidance that yields better, more informed decisions. This subject introduces quantitative methods to optimise the decisions to be made in the context of supply chain and logistic systems. Each method will be illustrated with real world case studies. Participants will learn to verify and enhance existing operating models.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
Basic knowledge of Supply Chain and Logistics, and familiarity with Excel is recommended.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
Traditional methods for transport planning have been widely used for the past age, however more and more transport researchers and planners have realised the shortcomings of classic methods in the digital age where historical and real-time data from various digital sources, such as GPS, smartphones, smart cards and Bluetooth sensors, are more readily available for better transport planning. Moreover, compared to traditional transport modes (e.g. bike, car, bus and train), more options (like autonomous vehicle, electric vehicles, connected vehicle, and scooter) are emerging to provide solutions to unsolved problems as well as to post new challenges in planning for their impacts on the demand for urban transport. It is however necessary to revisit the essentials of urban transport planning to understand the effective use of digital data and new technologies, and how they can be used for providing smarter mobility solutions. This short course will provide transport researchers and planners with basic knowledge of transport planning process, as well as major innovations and changes at the digital age. Multiple case studies will be shared with audiences as references for modern urban transport planning. The course will include a mixture of lectures and case studies throughout all 3 days planning.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
Basic knowledge of Transport Planning and Data Analytics is preferred but not required.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
Societies, modern cities and urban infrastructure systems are becoming more complex, interconnected, and difficult to optimise, control and manage. Agent-based modelling (ABM) offers a new lens to understand and steer the functioning of these systems by conducting experiments on artificial societies of computer agents. The course will begin by introducing fundamental principles of complexity and the dynamics of complex adaptive systems. A structured process to conceptualise, design, build, analyse, and validate ABMs will then be explained and illustrated using real-world examples. The course will draw on applications in a wide variety of social, urban and infrastructure problems, to help illustrate the power of ABM as an effective and accessible tool to understand why systems don’t always behave as expected and what can be done to improve them.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
Basic knowledge of modelling and simulation is preferred but not a requirement.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
The evolution of Systems Engineering into using model based tools has resulted in a range of benefits from greater traceability of information within a project to better informed decisions. Model-based Systems Engineering (MBSE) is a refinement of the traditional Systems Engineering practice to bring the information into a common model. To support MBSE, the Object Management Group (OMG) and the International Council of Systems Engineers (INCOSE) collaborated to develop the Systems Modelling Language (SysML). This course will introduce the MBSE concepts utilising SysML as the modelling paradigm. The course subsequently expands upon the understanding of SysML to see how broader and more complicated concepts are captured.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
A knowledge of Systems Engineering principles is preferred but not required.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
AWS Academy Cloud Foundations is intended for students who seek an overall understanding of cloud computing concepts, independent of specific technical roles. It provides a detailed overview of cloud concepts, AWS core services, security, architecture, pricing, and support.
Delivery
This course is delivered in person.
Duration
21 hours over 3 days.
Entry requirements
This is an entry-level course, but students should possess a general IT technical knowledge and general IT business knowledge.
Course credit
This course is part of the SMART Short Course series. Upon completion of three courses from the SMART Short Course series participants will be eligible to apply for credit equivalent to one standard subject (6 credit points unspecified) in any Bachelor or Master degree offered by the Faculty of Engineering and Information Sciences which includes space for a general elective. The UOW Credit for Prior Learning Policy and Procedures will apply.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the SMART Infrastructure Facility for fee information.
More information
Course overview
One-third of adults and half of all children who are admitted to hospital and who require peripheral intravenous catheters (PIVCs) are reported to have difficult venous access (DIVA). This microcredential will provide you with the knowledge to assess people with DIVA and the skill to insert PIVCs for infusion therapy, blood sampling and/or peripheral blood culture collection using assistive technology such as ultrasound.
Delivery
The microcredential is delivered in two parts: Five self-paced online modules (Part 1) and a full-day in-person practical workshop, which is delivered by clinical experts in vascular access (Part 2).
Duration
The course runs over 7 - 8 weeks during which you complete five self-paced online learning modules, attend a full-day workshop and complete a reflective assessment. Your total time commitment is approximately 50 hours.
Entry requirements
To be eligible for admission in this microcredential you must be currently accredited by your facility/clinic to insert PIVCs and perform phlebotomy.
Course credit
This microcredential represents 2 credit points towards a 6 credit point subject. To be eligible for credit towards an award course this microcredential must be combined with additional study that equates to at least 6 credit points. Partial credit cannot be awarded. The combined stack of microcredentials can be used to apply for unspecified credit towards a postgraduate award course where the course rules allow it.
Credentials
Upon completion of all learning activities and assessments you will be awarded with a digital Certificate of Attainment, which you can download and/or share online and via social media.
Course fee
$550 including GST.
More information
Course overview
The Gerontological Nursing Competencies (GNCs) is an evidence-based mentorship programme for registered nurses working with older people. The programme is delivered as an interactive workshop (virtual) complemented with online learning activities. There are two courses offered in a sequential pathway: (1) Essential GNCs Course and (2) Enhanced Leadership GNCs Course. As well as facilitation by gerontological researchers in the workshops and online, every participant is allocated an expert mentor from practice to provide support and guidance throughout the course. At the end of the programme, participants will attain specialised gerontological nursing knowledge and skills required to work effectively with older people and their families. The outcome of completing the GNCs programme is a portfolio of evidence for essential or enhanced level of specialist practice. The GNCs programme provides a career pathway for new graduates, early career and experienced registered nurses working in community, acute and residential aged care. The evidence in the portfolio will be a combination of work-based and professional development activities.
Delivery
This course is delivered online via virtual workshops, complemented with online learning activities.
Duration
Approximately 90 hours over 6 months.
Entry requirements
This course is open to new graduates, early career and experienced registered nurses and, with prior agreement, experienced enrolled nurses. A Bachelor degree in nursing as well as experience of working with older people in community, acute or aged care settings is required. Proficiency in English is essential as this course is delivered in English.
Course credit
On completion of this short course and submission of the portfolio, learners may apply for 6 credit points of specified credit (equivalent to one subject) towards a relevant postgraduate award course offered by the Faculty of Science, Medicine and Health. The specified credit will be for SNPG955 Dementia Care Across Settings or SNPG956 Policy and Practice in the Care of Older People and can be applied to courses such as the Graduate Certificate in Dementia Care or the Graduate Certificate in Gerontology and Rehabilitation Studies.
Credentials
On successful completion of the course participants will receive a Certificate of Attainment.
Course fee
Please contact the GNC team for fee information.
More information
https://www.adhere.org.au/gerontological-nursing-competencies