- Unix and C Programming
- Computer Systems
The Diploma of Information Technology addresses a significant market demand for skills associated with the design of distributed computing environments and the networks that underpin them.
Learn about computer technology, hardware and software, as well as computer communications and network management. Study the fundamentals of programming and theoretical knowledge of computing.
Available majors include:
*Progression hurdle applies for articulation into Bachelor of Computing
Students must complete the following core units:
Students must complete the following core units and course specific units where applicable:
Units may not be offered in every study period. Please contact your Program Manager for further information Computing@curtincollege.edu.au
Stage 2 Units – 25 Credit Points Each
This unit introduces the concepts and practices in Computer System Administration that includes Historical perspective, functions and basic concepts of network operating systems (OS) and real-time OS. The units also introduce the understanding of the role and configuration of network services including remote access and directory services, NOS installation planning, Linux installation and troubleshooting, understanding and implementing basic scripts (BASH) for system/network administration.
This unit aims to develop the knowledge and skills necessary to create computer programs that are capable of efficiently handling, storing and searching data using mathematical techniques applicable to the computing field at large. You will learn general computing structures and algorithms and will implement your code in Python and/or Java.
This unit introduces the core information security principles of confidentiality, integrity and availability. These core principles will be applied to the concepts of information risk management and the analysis and handling of compromised systems. The ethics around computer crime, privacy, and intellectual property are covered in detail. Finally, the unit will cover the criteria and controls for information classification.
This unit has been developed as an introduction to programming for science and particularly data science students. It responds to an increasing focus on data analytics and computational science in research and industry. Coding is also one of the valuable tools and skills covered as a valuable skill to apply and extend in your later studies and careers.
This unit introduces students to the importance of different cultural perspectives in science with an emphasis on the knowledge and experience of Australia’s Indigenous peoples. It also considers how culture shapes knowledge and explores the knowledge of Indigenous Australians in more depth (foregrounding Indigenous voices). The unit also explores how western science has attempted to erase this Indigenous experience and ownership, and the resulting human and environmental consequences. It reviews major global challenges and explores how genuine respect for, and integration of, Indigenous knowledge around the world can offer sustainable solutions. Students are invited to reflect on how the decolonisation of science and broadening perspectives around different knowledge systems can add value to their own scientific careers.
This unit provides students with an overview of Software Engineering
and introduces students to the fundamental concepts underlying Software Engineering. Topics covered include: Software life cycle models, requirements analysis and specification, measuring software quality, project management issues, software testing and maintenance and agile modelling techniques.
This unit develops the knowledge and skills necessary to understand both the power and limitations of Linear Algebra and Statistics in consideration of problems arising from engineering-related fields. Descriptive statistics and inferential statistics, vectors, matrices and their use for solving systems of linear equations, lines and planes and their extension into n dimension space would be explored to model and solve problems
This unit introduces students to the ‘C’ programming language and the related concepts and tools used to design, implement, test and debug ‘C’ programs. Topics covered include: ‘C’ Fundamentals. Functions and program structure. Designing programs with derived types. Pointers. Abstract data types. Strings, streams and input/output (1/0). Dynamic memory allocation and ‘C’ programming utilities for program construction and diagnosis.
This unit provides a mathematical introduction to statistical inference - drawing conclusions about the world using data in the presence of uncertainty. We begin with probability concepts, random variables and probability distributions. This provides the foundation for statistical inference. The unit incorporates both theoretical and practical methods. Students are introduced to the R statistical computing package, which is used widely in industry, commerce, research and further statistical studies. Students will take a big step towards statistical literacy, becoming critical and knowledgeable consumers of statistical reporting in media and scientific literature, and acquire a firm foundation for further studies in statistics.
This unit focuses on nonparametric methods and regression modelling which are both very important in statistical modelling of complex systems. Nonparametric methods are more flexible to some extent with less assumptions compared to the parametric methods. Simple linear and multiple linear regression as forms of predictive modelling techniques are aimed to examine the relationship(s) between a dependent (outcome/response) and independent variable(s) (predictor(s)).