Units you can study
Choose from the undergraduate or postgraduate options on offer across a range of disciplines. As long as you meet the prerequisites, you can choose subjects from any of our discipline areas to suit your interests.
Most units have a lecture and a tutorial each week. Lectures and tutorials for postgraduate units are usually held in the evenings.
Approved units
All students can study these units, regardless of your academic background. These units will be approved on your QUT study plan after you apply.
Mathematical sciences
DSB102 Introduction to Machine Learning
This unit introduces you to foundational concepts in statistical machine learning, equipping them with essential skills to handle and analyse complex data. You will explore both supervised and unsupervised learning techniques, starting with linear regression and advancing to methods like decision trees, support vector regression, and introductory neural networks. Additionally, the unit covers essential clustering techniques and simple yet practical machine learning applications suitable for first-year data science students. Through a combination of lectures, tutorials, and both individual and group assignments, you will engage deeply with real-world problems, and have the opportunity to benefit from diverse perspectives and career supports to develop their employability. You will be prepared to apply these methods and use industry-relevant digital practices to a range of real-world data problems and lay the groundwork for advanced studies in data science.
DSB200 Applied Data Science
Thanks to information technology, data has become the life blood of human endeavour. Individually and collectively, we depend on digital data to live well and flourish. This is because (even though data are merely symbols that can carry or store information) we can turn data into information, knowledge and wisdom that we can preserve, share and apply. Data Science is all about making sense of the information that data may hold to help us understand our Universe and act wisely to deliver benefit and avoid harm. Applied data science is where we bring abstract concepts, theories, methods and algorithms to bear on real-world data to inform human decisions and actions.
MAB141 Mathematics and Statistics for Medical Science
This introductory unit is designed to meet the mathematical and statistical requirements of medical science students, particularly students enrolled in Vision Science (OP45). Approximately one quarter of the unit focuses on the mathematical foundations for techniques used in manipulating medical science laboratory data. The remainder of the unit considers a range of relevant statistical techniques, addressing concepts such as which analysis methods may be appropriate for testing a given research hypothesis, how the choice of analysis method is affected by the available data and how to interpret the outcome of the formal analysis. This unit will provide you with an essential foundation in the mathematical and statistical concepts and data analysis methods that will be used in later medical science units.
MXB100 Introductory Calculus and Algebra
This unit builds on high school calculus by exploring derivatives, integrals and differential equations. It also introduces the basic theory of matrices, vectors and complex numbers. The ability to apply these concepts and techniques, and express real-world problems in mathematical language, is essential in quantitative fields such as science, business and technology. This is an introductory unit, which attempts to establish foundational skills that you will extend in subsequent discipline-specific units. This unit is particularly intended for students whose mathematics preparation does not include Queensland Senior Specialist Mathematics, Mathematics C or an equivalent.
MXB103 Introductory Computational Mathematics
Many real world phenomena are modelled by mathematical models whose solutions cannot be found analytically. To solve these problems in practice, it is necessary to develop computational methods, algorithms and computer code. This unit will introduce you to numerical methods for addressing foundational problems in computational mathematics such as solving nonlinear ordinary differential equations, finding roots of nonlinear functions, constructing interpolating polynomials of data sets, computing derivatives and integrals numerically and solving linear systems of equations. This is an introductory unit providing foundational skills in computational methods and their practical implementation using relevant computational software. This unit will be essential throughout the remaining parts of your degree. MXB226 Computational Mathematics builds on this unit by extending your computational and programming skills to more challenging problems and more sophisticated algorithms.
MXB105 Calculus and Differential Equations
Calculus and differential equations are used ubiquitously throughout mathematics, statistics and operations research. In this unit, you will build upon the foundations of calculus established in high school or in earlier university mathematics study, to greatly enhance your repertoire of theory and practice in these areas. The application of calculus and differential equations in the description and modelling of real-world problems will also be considered. This unit will extend your problem-solving skills, range of knowledge and use of techniques in differential and integral calculus. These theoretical concepts and their applications will be pursued further in MXB202 Advanced Calculus.
MXB106 Linear Algebra
This is a foundational unit in linear algebra which introduces core algebraic concepts, as well as theoretical and practical tools, that will be of central importance to solving real-world problems in science and engineering by mathematical methods. Linear algebra is fundamental to most branches of mathematics, finding widespread applications in mathematical modelling, statistics, machine learning, finance, economics, information technology, operations research, and computational mathematics. This unit aims to cultivate a deep understanding of the basic mathematical structures of linear algebra, including vector spaces and linear combinations, matrix transformations, invariant subspaces and eigenvalue problems.
MXB109 Introductory Operations Research
Operations Research (OR) is a mathematics discipline focused on decision-making. Operations research provides foundation and methods to determine how best to design, operate, manage, and predict behaviour of complex systems. The cornerstone of operations research is formulating and solving mathematical and computational models to find optimal decisions. This unit is students' first opportunity to explore foundational operations research methods and techniques to solve management and optimisation problems. In this unit we provide the theoretical foundation for future studies in operations research, building upon students' growing knowledge of linear algebra. This unit aims to develop students’ ability to apply various operations research methods, algorithms, and techniques to tackle practical, real-world problems in contexts such as the environment, agriculture, industry, finance, and healthcare.
MXB161 Computational Explorations
This unit introduces you to techniques of computation and simulation across a range of application areas in Science, Technology, Engineering and Mathematics (STEM). Computation and simulation are cornerstones of modern practice across STEM; practitioners skilled in these areas can explore behaviours of real-world systems that would be impractical or impossible to undertake using only theoretical or experimental means. In this introductory unit, you will develop your computation and simulation skills through individual and collaborative problem-solving activities. Depending on your course, further exploration may be available through a minor in this field.
MXB202 Advanced Calculus
Advanced calculus is fundamental to the study of applied mathematics and related quantitative disciplines such as physics, physical chemistry and engineering. This unit introduces you to new skills and methodologies in multivariable and vector calculus that are essential to the study of science, technology and engineering, and it also provides you with the necessary background to go on to more advanced study in applied mathematics, such as partial differential equations and advanced mathematical modelling. This unit builds on your introductory calculus and linear algebra skills developed in MXB105 Calculus and Differential Equations and MXB106 Linear Algebra, and will further develop your ability to decompose complex problems into smaller components, resolve these smaller components and hence solve the original problem.
MXB226 Computational Methods 1
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.
MXB241 Probability and Stochastic Modelling 2
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.
MXB325 Modelling with Differential Equations 2
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.
MXB334 Operations Research for Stochastic Processes
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.
MXB362 Advanced Visualisation and Data Science
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.
MXN600 Advanced Statistical Data Analysis
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
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.
QUT009 QUT You: Data Science for Society
Data is part of the fabric of our modern societies with almost all aspects of our lives influenced, for better or worse, by systems that are fundamentally data-driven. As individuals, we often unknowingly contribute enormous quantities of data to these systems through our use of smart devices, wearables, and online platforms. Understanding the power and limitations of the rapidly growing field of data science is more important than ever before. In this unit, you will identify sources of bias, error, and misinterpretation within the data science pipeline and the potential consequences of data-driven decision-making if these sources are left unchecked. This grounding in fundamental principles of data science will empower you to think critically and ethically about these systems and how they affect us. Regardless of your career or discipline, you have a role to play in ensuring data-driven systems are built that align with our personal values and the values of our society.
Units requiring approval
Students need specific academic background knowledge to study these units, so we will assess your eligibility and determine if you’re able to take these units after you apply. We will let you know the outcome through the application portal as soon as possible.
Mathematical sciences
MXB261 Game Theory and Simulation for Decision-Making
With the growing importance of strategic decision-making in business and data science, understanding game theory is essential for analyzing competitive and cooperative interactions. This unit introduces the mathematical foundations of game theory and its applications in these fields. You will explore concepts such as Nash equilibrium, cooperative games, Bayesian games, and mechanism design, with a focus on computational techniques. Through hands-on simulations, you will model and analyze strategic interactions in real-world scenarios, including pricing strategies, auctions, network games, and resource allocation. The unit emphasizes the use of computational tools to study equilibrium behavior, optimization, and decision-making under uncertainty. By combining mathematical theory with computational practice, this unit equips you with the skills to design and analyze strategic decision-making models in business and data science applications.
Enrolment restrictions
Postgraduate students can't enrol in:
- first-year undergraduate core units
- postgraduate honours-level units, which change from year to year.
Enrolment in capstone units is generally not allowed, as these units require extended knowledge gained throughout the course of a full degree.
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