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Study online through Open Universities Australia. Explore all degrees, subjects and short courses now.

Artificial Intelligence

Information Technology Fundamentals

Scientific Computing

Inside Information Technology

Basic Statistical Computing Using R

Data Analytics for Cyber Security

Defensive Cyber Security and Procedures

Risk and Security Management

Offensive Cyber Security and Penetration Testing

Technologies: Digital Solutions

The subject provides an introduction to many AI sub-fields, including: expert systems, machine learning, natural language processing, computer vision, intelligent agents. Students will be exposed to state-of-the-art examples as well as emerging technologies and get practical experience of solving interesting problems in each of these sub-fields. The subject covers the definition of Artificial Intelligence and its subfields; introduces foundational logic and knowledge representation; and considers social, ethical, and philosophical consequences of the theory and practice of AI. Students will learn different perspectives on the approach to creating AI, its purpose, and its validity. The subject will highlight the increasingly important social and economic roles of AI and will feature guest lectures from research and/or industry experts to highlight current research directions and deepen students&#39; understanding of specific topics.

AI and Big Data are popular buzzwords that are generating significant interest by businesses in today’s digital world. Business managers are increasingly investing in these technologies with the hope that automation and access to more data can lead to cost savings, create new business opportunities and sustain competitive advantages. This subject seeks to demystify AI and Big Data for business managers and to engender critical reflection on the unintended consequences and ethical issues for businesses associated with the introduction of these emerging technologies.

Artificial Intelligence and Big Data Applications for Business

Students will be introduced to the rapidly expanding and influential field of information technology which comprises various types of technologies in computers (both hardware and software) and computer networks. It is therefore relevant to students in a wide range of disciplines: for examples, health sciences, business, engineering and technology. Students will be taught the fundamental principles of computer operations, different types of input/output and storage devices, computer networks including Local and Wide area networks, information systems, Database, the Internet, the World Wide Web and HTML. Students will acquire the knowledge and practical skills in information technology and be able to apply them to their field of study.

This subject introduces essential concepts and techniques of computing for conducting science, with special emphasis on the preparation and manipulation of data. We discuss the role of computers and computing tools in science and focus on the use of spreadsheets and other data manipulation tools. This subject introduces vital skills for tertiary learning and explores their relationship to success in future careers. Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (<a href="https://sdgs.un.org/goals" target="_blank">UNSDG</a>s) Industry, Innovation and Infrastructure

Build data and IT skills that you’ll use throughout your science degree and career. You’ll learn how to collect, prepare, and process data using computers. See how spreadsheets can enhance the efficiency and accuracy of your scientific research.

This subject introduces R, one of the popular open source statistical programming languages commonly used in applied statistics and data science disciplines. Students will learn key programming principles of R and develop competence in programming in R which are essential for a statistician or data scientist to perform different types of statistical analyses.This subject was formerly known as STA60003 Basic Statistical Computing

Upskill and package up your computer and statistical knowledge. Form questions. Use SPSS software to select, modify, merge and apply data visualisation techniques. Investigate missing values and manage complex data files. 

This subject aims to provide a broad introduction to the fundamentals of data communication and network technology. The emphasis is on higher aspects of data communication from the perspective of computer scientists and information technologists; the subject covers the underlying mechanisms and their characteristics that need to be considered by communicating application software.
Topics include:
<ul><li>principles and reference models of data communication;</li><li>basic operation of communication systems;</li><li>protocols and error handling, and applications in networked environments.</li></ul>

Learn how people, devices, information and services are continuously connected by an evolving data communications network. Gain critical analysis talent, uncover data communication methods, and reveal the drivers for adopting alternative technologies.

Data Communication and Net-Centric Computing

Cloud Computing is a large-scale distributed computing paradigm which has become a driving force for information technology over the past several years. The exponential growth data size in scientific instrumentation/simulation and social media has triggered the wider use of cloud computing services.This course covers topics and technologies related to Cloud Computing and their practical implementations. You should explore different architectural models of cloud computing, the concepts of virtualisation and cloud orchestration. You should gain hands-on experience with various features of popular cloud platforms such as Google App Engine and Amazon Web Service throughout the lectures, tutorials, and laboratory sessions. Advanced cloud programming paradigms such as Hadoop’s MapReduce is also included in the course. You should also learn the concept of modern Big Data analysis on cloud platforms using various data mining tools and techniques. The lab sessions cover cloud application development and deployment, use of cloud storage, creation and configuration of virtual machines and data analysis on cloud using data mining tools. Different application scenarios from popular domains that leverage the cloud technologies such as remote healthcare and social networks will be explained. The theoretical knowledge, practical sessions and assignments aim to help you to build your skills to develop large-scale industry standard applications using cloud platforms and tools.This course focuses on learning emerging issues related to Cloud computing technology. The objectives are:<ul><li>Understand various basic concepts related to cloud computing technologies</li><li>Understand the architecture and concept of different cloud models: IaaS, PaaS, SaaS</li><li>Understand big data analysis tools and techniques</li><li>Understand the underlying principle of cloud virtualization, cloud storage, data management and data visualization.</li><li>Understand different cloud programming platforms and tools</li><li>Have details knowledge on reading and writing in cloud storage</li><li>Be familiar with application development and deployment using cloud platforms</li><li>Create application by utilizing cloud platforms such as Google app Engine and Amazon Web Services (AWS)</li><li>Learn to develop scalable applications using AWS features.</li><li>Learn basic concepts of MapReduce programming models for big data analysis on cloud.</li></ul>

Round off your IT course with an exploration of cloud platforms, apps, and databases. Elevate your coding to include advanced cloud programming. Unpack big data and cloud storage. Complete problem-solving tasks and gain hands-on experience.

Cloud Computing

Entrepreneurship is an essential element of today’s society. This subject will outline the basic principles of Entrepreneurship. It will examine the steps required in developing an idea into a business and will explore the tools and necessary insights to make a successful venture. You will interpret and employ theory to case studies. Guest speakers will present and discuss start-up issues, pitfalls, and the ingredients for success. You will also develop professional skills related to ethical and moral decision making and evaluate the social implications of their work and the broader global context.

Professional Practices and Entrepreneurship in Information Technology

This course will take you from the history of computers, through the basics of their design, into the role and structure of operating systems, and will finish with a focus on programming and comparative programming languages.Your course content is heavily informed by industry needs and will lay a solid foundation to help launch your career in IT.  UniSA Online’s 10-week short courses give you the flexibility to up-skill in a certain area, stay current with developments in your field, diversify your knowledge, or even explore a new direction in your career – without having to commit to the time and cost of a full university degree.Delivered 100% online, you’ll be able to study where and when it suits you. Access online academic and student support seven days a week, fit study around work and life commitments, view learning resources 24/7, and log in to the interactive online environment anywhere, any time and on any device.This is a first-year course from UniSA Online’s Bachelor of IT and Data Analytics degree.Should your course have an exam it will be scheduled for Australian Central Standard Time or Australian Central Daylight Time, depending on the time of the year.

Dive into the history of computers. Look at the basics of their design, the structure of operating systems and more. Move onto programming. Learn skills to launch your career in IT.

This course is an introduction to computing ethics, law and employability. It is intended for computing students who have not studied business principles, or who have little work experience in industry. The course provides a survival kit for computing graduates entering the workforce. During this course, you should consider computing ethical issues, such as information privacy, computer crime, computer security, social networks, online identity. During this course, you should also consider the international legal frameworks available to protect software system development. This includes non-disclosure agreements, employment contracts, intellectual property law (copyright, patents, licensing, royalties), trademarks and warranty disclaimers. Additionally, you should examine the marketing of a software system development, involving SWOT analysis and action plan.

Gain commercial insight into computing ethics, law and marketing in a professional, technical setting. Dig into the dark corners of malware, computer crime and terrorism. Study privacy, patents, royalties and global laws protecting software systems.

Professional Computing Practice

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