Found 1159 study abroad units
MXB225 Modelling with Differential Equations 1
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Differential equations are commonly used to formulate mathematical models of real-world phenomena from across science, engineering, economics and beyond. This unit builds on your earlier studies of differential equations to consider how such models are constructed, how to obtain analytical solutions, and how to use these models and their solution to gain insight into real-world processes.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB226 Computational Methods 1
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
This is a foundational unit for Computational Mathematics. It introduces the design and implementation of computational techniques for solving a range of problems in mathematics. These techniques will be analysed for important properties such as efficiency, stability, convergence and error. The main topics that will be covered include: finite difference methods for models of heat diffusion in two dimensions; direct and iterative methods for linear systems; efficient storage of data; norms; approximation; numerical integration; numerical methods for ordinary differential equations.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB232 Introduction to Operations Research
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Operations Research (OR) is a mathematical approach to decision making. The predominant goal of OR is to determine how best to design, operate, manage, and predict behaviour of complex systems. The cornerstone of OR is formulating and solving mathematical or computational models to extract the best, or optimal, decisions. The purpose of this introductory unit is to introduce students to foundational OR methods and techniques to solve management and optimisation problems. It provides the theoretical foundation for future studies in OR and builds upon earlier studies in linear algebra. This unit aims to develop students’ ability to apply various OR methods, algorithms, and techniques in the solution of practical, real-world problems in contexts such as the environment, agriculture, industry, finance, and healthcare.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB241 Probability and Stochastic Modelling 2
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
It is important to develop skills and knowledge in both statistics and mathematics. Building on the methodology and skills developed in previous studies in probability and stochastic modelling, this unit provides you with formal statistical tools such as stochastic process models and statistical methods for theoretical and applied development. These methods are useful in a wide range of areas, from communication systems and networks to traffic to law to biology to financial analysis, and link with other modern areas of mathematics. This unit will provide opportunities to learn how to build statistical models of real world processes, acknowledging the assumptions inherent in selected models. The skills developed in this unit will be integral in the understanding of material throughout your studies in statistics and mathematical modelling.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB242 Regression and Design
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
This is an intermediate applied statistics unit addressing the collection (design of experiments), exploration, summarisation, analysis and reporting of continuous data. You will analyse data using general linear models and communicate findings using oral and written methods. You will use mathematical and statistical software, such as R, to enhance your data analysis and develop your statistical programming skills. The application of statistical data analysis is pervasive across Engineering, Science, Health and Business. Hence, this unit is suitable for both Mathematics students and students in other disciplines. This unit is intended for students who have completed foundation studies in statistical data analysis and who wish to develop further skills in applied statistics. MXB344 Generalised Linear Models builds on this unit by considering the analysis of binary, categorical and count data. MXB343 Modelling Dependent Data extends this unit for data that are not independent.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB261 Modelling and Simulation Science
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
With the rapid development in both computing hardware and its application to advanced scientific problems that require computational solutions, there is a need for IT, Maths and Science students to have a practical understanding of Computational and Simulation Science. This unit aims to provide you with the knowledge to apply computational simulation techniques in a selection of application areas where the scientific problems are characterised by widely varying scales, both in space and time. You will use relevant programming softwares to develop and implement simulation algorithms together with analysis of resulting data using multi-dimensional visualisation techniques. You can further develop visualisation skills through units MXB262 Visualising Data and MXB362 Advanced Visualisation and Data Science, as well as extending your knowledge of computational science through the unit MXB361 Aspects of Computational Science.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB262 Visualising Data
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Our world has an unprecedented amount of available data - especially in STEM, where generating and working with data is core to our fields. The ability to visualise data is critical for exploring and communicating science and engineering findings. Modern visualisation theory and techniques allow us to efficiently explore and communicate with data. This unit introduces data visualisation concepts, theories, and techniques, along with practical experience exploring and dynamically visualising complex data. You will develop an understanding of the fundamental concepts in data visualisation through practical, real-world examples in contexts such as the environment, agriculture, industry, engineering, and healthcare. You will follow the visualisation pipeline from importing, to visualising, to communicating data. We focus on effective visual communication and high-quality, fit-for-purpose representations of 2D, multi-dimensional, network, and spatial data.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB322 Partial Differential Equations
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Partial differential equations are the foundation of mathematical models that describe evolving processes exhibiting spatial and temporal variation. In this unit you will learn how the study of such equations synthesises and extends many of the concepts you have learned previously in linear algebra and calculus. The powerful frameworks of Fourier analysis and integral transforms that underpin partial differential equations provide a means for obtaining solutions to a number of equations of unparalleled physical importance, and for understanding the behaviour of mathematical models more generally.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB325 Modelling with Differential Equations 2
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
Among the variety of differential equations encountered in applied mathematics, equations modelling the transport of quantities such as mass and energy are especially important. This unit significantly extends your repertoire by considering models with greater mathematical complexity than you have previously encountered, drawn from and representative of a variety of important real-world applications. Such complexity necessitates greater ingenuity in the analysis and solution of the governing equations, which will harness and extend your full knowledge of modelling with differential equations.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB326 Computational Methods 2
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Advanced computational methods underpin essentially all modern computer simulations of complex real-world processes. This unit will significantly extend your toolset of computational methods, particularly for the solution of complex partial differential equation models of real phenomena. You will gain critical expertise and experience at building practical, efficient computer codes which will leverage advanced theoretical and algorithmic considerations that draw upon your full range of mathematical and computational knowledge and skills in linear algebra and calculus.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB328 Work Integrated Learning in Applied and Computational Mathematics
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
Throughout your course, you have been building your discipline skills and your understanding of contemporary industry practice. This capstone unit provides you with the opportunity to bring together the skills that you have developed throughout the applied and computational mathematics major, combining them in a coherent manner to solve a significant and relevant real-world problem from industry. Your experience will reflect the genuine practice of an applied mathematician in the workforce.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB332 Optimisation Modelling
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Operations research techniques are used in numerous industries and are critical for decision making. These industries need graduates who can apply techniques of mathematical modelling, statistical analysis, mathematical optimisation and simulation and can implement these techniques using appropriate computer software packages. This unit will build upon the content of MXB232 by introducing more advanced “intermediate” level operations research methods and techniques. The topics addressed in this subject are vital in this field and are critical for advanced applications and studies in this field. Topics covered include: model building in mathematical programming, modelling language - (e.g. OPL, Gurobi or equivalent), integer programming and branch-and-bound method, introduction to inventory theory, dynamic programming; and computer solutions of advanced linear programming problems and their analysis.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB334 Operations Research for Stochastic Processes
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
This unit provides you with the opportunity to apply your knowledge and skills in operations research to guide decision-making for complex real-world problems. Your previous learning in deriving and solving operations research problems was mostly dealing with a decision making in a deterministic setting. The focus here is to optimize decision making when there is uncertainty and stochastic variables. Combined with the operations research expertise you have acquired over your degree, you will be able to formulate and solve these complex decision problems using computational tools.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB338 Work Integrated Learning in Operations Research
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
Throughout your course, you have been building your discipline skills and your understanding of contemporary industry practice. This capstone unit provides you with the opportunity to bring together the skills that you have developed throughout the operations research major, combining them in a coherent manner to solve a significant and relevant real-world problem from industry. Your experience will reflect the genuine practice of an applied mathematician in the workforce.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB341 Statistical Inference
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
This is an advanced unit in mathematical statistics covering the theory of point estimation and inference using both classical and Bayesian methods. Statistical inference is the practice of both estimating probability distribution parameters and using statistical testing to validate these results, and plays a crucial role in research, and many real-world applications. You will use the methods of least squares, moments, and maximum likelihood to construct estimators of probability distribution parameters and evaluate them according to criteria including completeness, sufficiency, and efficiency. Results will be computed both analytically and numerically using software such as R. You will learn and apply the Neyman-Pearson Lemma for the construction of statistical tests, including to real-world applications, and learn Bayesian statistics for finding posterior distributions of parameters and evaluating their performance. Results will be communicated both orally and in written form.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB343 Modelling Dependent Data
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
Unit synopsis
In many studies, observations can be correlated. For example, we often see temporal lingering effects over time in time series, or genetic effects in litters or repeated measures from patients in medical trials. This unit is about using statistical methodology to achieve efficient inference that appropriately takes into account dependencies in such datasets. Many examples and analysis using software such as R packages are involved.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB344 Generalised Linear Models
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
For data that arise in, for example, science and commerce, it is often unreasonable to assume they are continuous random variables from a normal distribution. It is likewise unlikely that data are handed to an analyst in a state ready for advanced statistical techniques. In this unit you will be introduced to modelling techniques and methodology for the explanation of non-normal data. You will also learn, by way of a realistic project, techniques to overcome common issues with shaping data for analysis. Hence, you will be well prepared in the application of appropriate statistical practice when such data are encountered in the real world.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB348 Work Integrated Learning in Statistics
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
Throughout your course, you have been building your discipline skills and your understanding of contemporary industry practice. This capstone unit provides you with the opportunity to bring together the skills that you have developed throughout the statistics major, combining them in a coherent manner to solve a significant and relevant real-world problem from industry. Your experience will reflect the genuine practice of a statistician in the workforce.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB361 Aspects of Computational Science
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
With the rapid development in computing hardware, algorithms, AI and their applications to advanced scientific problems that require computational solutions, there is a need for IT, Maths, Science and Engineering students to have a practical understanding of Computational Science. You will develop advanced knowledge and skills in computational techniques for solving real-world in numerical computing environments such as MATLAB. This unit aims to provide you with the knowledge to apply computational techniques for problem-solving in a variety of application areas you are likely to encounter in your early careers, whether in industry or in further study. This unit will equip you with an understanding of different application areas requiring modern computational solutions, particularly as they relate to complex systems; you will have the opportunity to implement such computational techniques and analyse and interpret the resulting data.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXB362 Advanced Visualisation and Data Science
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
Data visualisation is an essential element of modern computational and data science. It provides powerful tools for investigating, understanding, and communicating the large amounts of data that can be generated by computational simulations, scientific instruments, remote sensing, or the Internet of Things. The aim of this unit is to explore the issues, theories, and techniques of advanced data visualisation. This unit develops theoretical and practical understandings of the major directions and issues that confront the field. A selected number of advanced data visualisation techniques will be examined in detail through specific examples. The practicals will reinforce lecture content and extend your applied skills and knowledge in data visualisation, including specific methods. A focus of the unit is the development of real world data visualisation skills and experience, based on a major data visualisation case study.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
MXN500 Introduction to Statistics for Data Science
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Postgraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Statistics forms the foundation of many tools and techniques used in data analytics. Therefore, appropriate application of statistical methods is essential in many quantitative roles and data science applications. The focus of this unit is on applying statistical methods in real-world contexts. You will look for meaningful patterns and model data to increasing levels of complexity. We will cover data and variables, visualisation, introductory probability, hypothesis testing, and linear regression. You will also learn how to select and apply appropriate quantitative methods using software such as R, an open-source statistical software. You will practice your quantitative skills using real data from scientists, business, and governments. This unit is appropriate for those requiring an introduction to, or a refresher in, statistics. The concepts in this unit are extended upon in MXN600.
MXN600 Advanced Statistical Data Analysis
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Postgraduate units
- Availability
- Semester 2 (July)
Unit synopsis
This advanced statistics unit will introduce modern statistical methods of data analytics that are frequently used in industry and government to solve real-world problems. It introduces modelling techniques that can be used when it is unreasonable to assume the data are continuous random variables from a normal distribution and/or that the expected value of the random variable can be modelled as a linear combination of regression parameters. This is a Masters level unit, and the knowledge and skills developed in this unit are relevant to those studying advanced data analytics. Further studies in data analytics and data science will most likely build on this unit by extending your analytical skills through industry or research-based projects.
MZB125 Introductory Engineering Mathematics
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February) and Semester 2 (July)
Unit synopsis
Professional engineers have a "conceptual understanding of the mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline" (Engineers Australia Stage 1 Competency Standard for Professional Engineer). This unit will serve as the transition from high school mathematics to university, particularly if you have not studied Queensland Specialist Mathematics (formerly called Senior Mathematics C) or equivalent. You will learn about elementary functions, their derivatives and integrals, the algebra of complex numbers, and vectors and matrices. Mathematical techniques and problem solving skills are employed in a range of mathematical exercises and contextualised problems, illustrating how these concepts and techniques are used in engineering systems. In future units you will continue to apply the mathematical knowledge and skills you have learned in this unit to increasingly complex problems.
NSB102 Professional Practice and Cultural Safety
Unit information
- School/discipline
- School of Nursing
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
As healthcare providers, nurses need knowledge, skills, and attributes to implement culturally safe, person-centred, inclusive care for people from all backgrounds across the lifespan. To meet regulatory requirements, ethical, professional, and quality standards, this foundational unit introduces cultural safety as a model underpinning professional nursing practice. Knowledge of the impact of our own cultures and those of professions and systems is essential to provide inclusive nursing care that is respectful and compassionate, free of racism, stigma, and other forms of discrimination across all practice settings. This unit introduces social determinants of health that underpin cultural safety, societal responses to diversity and the impacts of these responses on health. The significance of nurses providing culturally safe care that improves peoples' health outcomes is emphasised throughout the unit.
NSB103 Health Assessment
Unit information
- School/discipline
- School of Nursing
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Health assessment is the foundation of nursing practice and clinical reasoning. This unit complements the unit LQB185 Anatomy and Physiology for Health Professionals by providing an opportunity for you to apply knowledge of scientific foundations of human health to the core nursing skill of health assessment (observation, interview, measurement, and physical examination). Effective health assessment underpins all aspects of person-centred nursing care. The foundational skills learnt in this unit are critical to success in later integrated-practice units and unit concepts are further developed as students extend their knowledge of health and nursing. Selected Principles of Public Safety and Quality Health Standards and Aged Care Standards are integrated.
NSB132 Integrated Nursing Practice 1 On campus
Unit information
- School/discipline
- School of Nursing
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
This beginning-level unit aims to establish cognitive skills in clinical reasoning which inform provision of safe, person-centred, and evidence-based nursing practice. This unit directly links to subsequent Integrated Nursing Practice units. Unit learning activities develop your understanding of the nurse role and skills in clinical reasoning relevant to fundamental care provision. Practice reflecting the Aged and Quality Standards is a particular focus, and this is then further explored and consolidated in subsequent integrated nursing practice units.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
NSB202 Aboriginal and Torres Strait Islander Peoples' Well-being
Unit information
- School/discipline
- School of Nursing
- Study level
- Undergraduate units
- Availability
- Semester 1 (February) and Semester 2 (July)
Unit synopsis
An understanding of the social determinants of health and the impact of historical and contemporary policy and practice influencing the health and well-being of Aboriginal peoples and Torres Strait Islanders is essential to providing optimal health care. This unit privileges cultural safety as the preferred model to contemporary health care delivery in Australia. It promotes the position of the contemporary health practitioner as a fundamental member of the partnership with the health care recipient, and thus is necessary to enhancing Aboriginal and Torres Strait Islander health and well-being. Cultural safety also makes conspicuous manifestations of racism which impact on Aboriginal and Torres Strait Islander health and well-being. Importantly, a culturally safe approach values the pivotal role of Aboriginal peoples and Torres Strait Islander peoples' self-determination in leading health care advances associated with their own care.
NSB203 Inquiry in Clinical Practice
Unit information
- School/discipline
- School of Nursing
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
This unit at a developmental level of your course, explores inquiry in clinical practice by examining the role of evidence-based practice and application of research processes in nursing practice further synthesised in your final year. Skills in interpretation of evidence will be developed and an overview of various approaches to research are examined to enable students to be effective consumers of research. The relationship between research, evidence, and safety and quality in health care is explored. This knowledge is foundational to all remaining units in the course. Contemporary nursing work requires the ability to seek, interpret, analyse, synthesise, and integrate evidence into practice. The facilitation of ongoing improvement in nursing practice requires critical thinking, broader perspectives, and decision making informed by evidence.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
NSB204 Mental Health: Self and others
Unit information
- School/discipline
- School of Nursing
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
This unit focuses on the National Health Priority of mental health and explores the social determinants, legislation and policies that inform nursing care provision. Mental health issues are a universal human experience across the lifespan and affect one in 4 Australians. In this unit, learning activities embed the concepts of recovery and cultural safety as well as trauma informed care in promoting positive messages that challenge stigma and discrimination. Emphasis is given to the development of the professional self and attributes of trust, rapport building, and a non-judgemental approach to practice. Focus is also given to developing skills in assessing and responding to people who experience symptoms of mental illness. This includes history-taking, mental state, and risk assessment, while utilising the recovery framework.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.
NSB231 Integrated Nursing Practice 2 On campus
Unit information
- School/discipline
- School of Nursing
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
This unit is at the developing stage of the course and builds on preceding units. You are expected to draw on knowledge and skills gained in previous units to enhance your understanding of nursing practice and peoples’ experience of health and illness. Peoples’ experiences of the continuum of care in different contexts of health care are emphasised to highlight chronic and acute dimensions of illness using unfolding clinical cases. The unit also has a synergetic relationship with the NSB232 Integrated Nursing Practice 2 – Off campus unit, and units are co-requisites. A thorough understanding of the NMBA Registered Nurse Standards for Practice, National Health Priority Areas, and National Safety and Quality Health Service Standards is essential to nursing practice and will underpin success in this unit. Face-to-face teaching, particularly tutorials may commence in 0 week. Please refer to the published timetable.
Approval required
You can only enrol in this undergraduate unit if you meet the specified requirements and have significant background knowledge in the area of study. After you apply, we will assess the units and your background knowledge and let you know the outcome.