Found 228 study abroad units
IGB283 Game Engine Theory and Application
Unit information
- School/discipline
- School of Computer Science
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
This unit will introduce you to the mathematics for computer graphics and games. Instead of just teaching mathematics, this unit focuses on taking mathematical theory and learning to program small examples in a game engine. The core parts of any game engine are the mathematical representations and algorithms. This unit will give you a basic understanding of the mathematics behind 3D graphics and games and the ability to apply the theory to solve problems in game engine development and software development in related areas. This unit will provide you with foundation knowledge and skills for programming and using 3D game engines. It is a pre-requisite for following advanced units that will build on these skills to provide you with enough knowledge to develop your own game engine and to have a deeper insight into popular commercial engines and tools used in the course.
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.
IGB321 Immersive Game Level Design
Unit information
- School/discipline
- School of Computer Science
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
Level design is a critical, key component to any video game, no matter how abstract or realistic. It is crucial that a level designer has the ability to lay out levels, construct levels within the game engines, plan gameplay scenarios and place non-player characters. This unit will help students develop these abilities as well as skills such as building terrain, building architecture and spaces, balancing gameplay, integrating narrative elements and goals, playtesting and implementing iterative design improvements, designing lighting and atmospheric effects and other genre-specific level design skills using the Unreal game engine. Students are expected to have some degree of high level game design skills and preliminary scripting abilities for this unit.
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.
IGB383 AI for Games
Unit information
- School/discipline
- School of Computer Science
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
The core concepts, principles and practices of designing and implementing Artificial Intelligence (AI) within computer games are explored and implemented within this unit. The introduction of modern theoretical models as well as commercial examples provides a foundational understanding of both the history and future of Game AI. This is particularly important when designing natural and/or humanistic behavioural effects of Non-Player Characters (NPC). Knowledge and skills developed during this unit adhere directly to modern Game and AI development and are required of industry practitioners today. You will develop an understanding of the field and develop expertise in addressing modern Game AI algorithms and problems.
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.
MAB141 Mathematics and Statistics for Medical Science
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
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.
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.
MXB100 Introductory Calculus and Algebra
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February) and Semester 2 (July)
Unit synopsis
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.
MXB101 Probability and Stochastic Modelling 1
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
This unit introduces probability and shows you how to apply its concepts to solve practical problems. The unit will lay the foundations for further studies in statistics, operations research and other areas of mathematics and help you to develop your problem-solving and modelling skills. The topics covered include: basic probability rules, conditional probability and independence, discrete and continuous random variables, bivariate distributions, central limit theorem, and introduction to Markov chains. This unit is appropriate for those requiring an introduction to, or a refresher in, probability. The concepts in this unit will be extended in MXB241.
MXB102 Abstract Mathematical Reasoning
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Mathematics is, at its heart, axiomatic: each new mathematical statement follows logically from previous statements and ultimately derives from the axiomatic foundations. This unit establishes the foundations of abstract mathematical reasoning, introducing the view of mathematics as axiomatic and emphasising the role of proof in mathematics. Fundamental concepts and tools including logic and sets, number systems, sequences and series, limits and continuity are covered. The tools established in this unit will serve as a foundation throughout your mathematics studies.
MXB103 Introductory Computational Mathematics
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
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 Methods 1 builds on this unit by extending your computational and programming skills to more challenging problems and more sophisticated algorithms.
MXB105 Calculus and Differential Equations
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February) and Semester 2 (July)
Unit synopsis
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
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February) and Semester 2 (July)
Unit synopsis
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, 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. These theoretical concepts and their applications will be pursued further in MXB201 Advanced Linear Algebra.
MXB107 Introduction to Statistical Modelling
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
Statistical modelling provides methods for analysing data to gain insight into real-world problems. The aim of this unit is to introduce a wide range of fundamental statistical modelling and data analysis techniques, and demonstrate the role they play in drawing inferences in real-world problems. This unit is designed around the exploration of contemporary and important issues through the analysis of real data sets, while simultaneously and necessarily building your statistical modelling expertise. You will learn how to propose research questions, analyse real data sets to attempt to answer these questions, and draw inferences and conclusions based on your findings. The importance of ethical considerations when dealing with real data sets will be emphasised. The R programming language will be introduced, and you will gain experience and build your expertise in using this industry-leading software to conduct statistical analyses.
MXB161 Computational Explorations
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February) and Semester 2 (July)
Unit synopsis
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. Further exploration is available through the second major or minor in Computational and Simulation 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.
MXB201 Advanced Linear Algebra
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 1 (February)
Unit synopsis
Much of the power of linear algebra stems from its widely-applicable collection of analytical tools for applied problem-solving. This unit builds upon your knowledge of linear algebra to explore more advanced techniques and applications of matrices and vectors. Furthermore, you will learn how much of what is familiar about linear algebra in Euclidean space can be abstracted to develop a more generally applicable theory. Hence you will develop an appreciation for the power and versatility of linear algebra across the mathematical sciences.
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.
MXB202 Advanced Calculus
Unit information
- School/discipline
- School of Mathematical Sciences
- Study level
- Undergraduate units
- Availability
- Semester 2 (July)
Unit synopsis
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.
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.
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.