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Bachelor of Computer Science/Master of Data Science (Online) curriculum

Curriculum Details

  • 32 units
  • 320 credit points
  • 4 years full-time online study

You can complete ACU’s Bachelor of Computer Science/Master of Data Science (Online) in as little as four years with full-time study. Delivered 100 per cent online, you can study around your existing commitments with convenience and flexibility. To graduate, you’ll need to acquire 320 credit points.

This course is offered over four 10-week terms per year. You’ll access your learning materials from the start of each term and progress at your own pace. Some courses require on-campus intensives or in-person placements.

If you have any questions regarding units, study options, course structure, or any other related concerns you can speak with an enrolment adviser on (02) 9158 7744 or schedule an appointment.

Computer Science specified units (170CP)

Credit points

In a rapidly evolving digital world, computing professionals must design technologies that are not only innovative but also ethical, inclusive, and socially responsible. This unit introduces students to the societal, cultural, and ethical dimensions of computing and explores how technology can address real-world problems or create value for communities and organisations.

Students apply user-centred and design thinking approaches to identify societal or business challenges, develop empathy maps and problem statements, and propose computing-based solutions such as mobile or web applications. The unit integrates concepts of cybersecurity, sustainability, and cultural inclusion, including respect for Australian Aboriginal and Torres Strait Islander perspectives, to promote ethical innovation. Aligned with the United Nations Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure), the unit challenges students to think critically about the kind of future we are building with technology.

The aim is to enable students to see themselves not just as learners of computing, but as future innovators, problem-solvers, and changemakers capable of using technology to serve the common good.

To work effectively in computer science roles, students must have a sound understanding of essential data structures and algorithmic techniques to build the foundation of intelligent, efficient, and ethically responsible software development.

This unit provides a critical foundation for advanced study in data science and other emerging technologies. Students gain hands-on experience with fundamental data structures—including arrays, linked lists, stacks, queues, hash tables, trees, and graphs—and learn to apply key algorithms for sorting, searching, recursion, and traversal. Students will evaluate algorithm efficiency using asymptotic notations and make informed decisions about time-space trade-offs in real-world computing scenarios.

Students will gain conceptual understanding of scalable methods for big data processing, with applications in areas such as healthcare analytics, digital health platforms, and medical decision-making. The aim of this unit is to introduce students to the principles of resource-aware computing and how technology can contribute to the common good, in alignment with the United Nations Sustainable Development Goal 3: Good Health and Well-being.

As emerging technologies continue to transform industries and societies, computing and data professionals are increasingly expected to demonstrate not only technical expertise but also ethical awareness, cultural sensitivity, and social responsibility.

This unit develops students’ ability to critically engage with professional ethics, legal frameworks, and the broader human implications of technological innovation. Students explore ethical theories, professional standards, and real-world dilemmas to strengthen their capacity for ethical reasoning and sound professional judgment. Learning activities encourage reflection on diverse perspectives and values, including those informed by Australia’s First Peoples’ knowledges and experiences, to support inclusive, equitable, and socially responsible practice. Through critical inquiry and applied learning, students build adaptability, communication, and leadership skills while deepening their understanding of how technology can serve the common good.

The aim of this unit is to prepare students to act with integrity, empathy, and professionalism as ethical leaders in dynamic and evolving digital environments.

In today’s digital age, nearly every piece of technology we use relies on a crucial component to function effectively: the operating system. This unit offers a comprehensive introduction to the fundamental concepts and principles of operating systems. Students will delve into various types of operating systems and explore essential topics such as process and thread management, memory management, file systems, and input/output systems. Students will build on their programming and systems knowledge to gain a deep understanding of both the theoretical and practical challenges involved in designing, implementing, and utilizing operating systems. The aim of this unit is to assist students to support organisations to function effectively through developing understandings of operating systems.

Computer networks are pervasive and vital to virtually all areas of our lives and support all modern computing activities. Computer networks are also inherent in nearly all modern computing systems. As such, they are the backbone of the function of society as they are critical to today’s communication systems and enable all online activities. Knowledge of computer networks is fundamental to many other areas of digital technology including cyber security, cloud computing and the Internet of Things.

This unit covers the essential elements of computer networks, equipping students with the skills and knowledge to navigate and contribute to our increasingly connected world. The aim of this unit is to support students to develop key knowledge and skills to enable them to design computer networks to support the needs of a range of diverse organisations.

To accommodate the needs of an increasingly mobile workforce and community, computer systems have become predominantly reliant of cloud-based data storage and computing. This unit provides an in-depth introduction to cloud technologies, architectures and services, focusing on the essential concepts and practical applications. Students will explore a range of cloud service models and architectural frameworks that facilitate cloud computing. Critical technologies that enable cloud services will be covered, as well as cloud security, compliance and best practices for designing applications and systems that use the cloud. The unit also addresses the process of evaluating cloud service providers and their offerings, equipping students with the skills to make informed decisions to meet real-world applications. The aim of this unit is to give students the skills to support development of cloud-based systems to support the needs of a diverse range of organisations.
Data is deemed as the world’s ‘new oil’ while data science is a new inter-disciplinary science of data that employs scientific methods, algorithms, tools and systems for uncovering insights, knowledge and value from massive data generated in different domains. Python, a general-purpose programming language, has gradually become the ‘engine’ of data and data science. In particular, many data scientists use Python because it provides a wealth of data science tools and libraries. This unit will cover fundamental elements of Python programming language and its comprehensive use in the context of data science. This includes Python language basics, data structures, functions, files, tools and various Python data science libraries for data processing, analysis and visualisation. Data ethics and elementary statistics and probability in data science will also be introduced. The aim of the unit is for students to learn how Python can be used for building data science solutions.
In the information age we live in, data is recognised as a vital asset for organisations. Databases have become an essential technology for the organisations to record, process and manipulate data and information efficiently, and preserving data quality and security. This unit will provide you with foundational knowledge and practical skills in database design and implementations. The unit further develops your practical skills in identifying and modelling organisational information requirements; developing using conceptual data models and verifying its structural characteristics with normalisation techniques; implementing and utilising a database using a Relational Database Management System (RDBMS) and Structured Query Language (SQL) to manipulate data and generate information. In addition, the unit introduces essentials of data security and quality management, and legal and ethical consideration in handling organisational data. The primary aim of this unit is to provide students with knowledge and practical skills needed to design, implement database solutions to address real-world needs of organisations while preserving data privacy and security to support the dignity of humans served by the organisation.
Data science is an inter-disciplinary area that employs scientific methods, algorithms, tools and systems for extracting insights, knowledge and value from data. Machine learning, as a core part of data science and data analytics, and a subfield of artificial intelligence, is the scientific study of algorithms and mathematical models that computer systems use to make decisions or predictions. Machine learning algorithms and models are widely used in human’s digital life such as email client, search engine, social media, virtual personal assistant and recommendation system, although machine bias is an important ethical concern of which many people are unaware. Python is one of the most popular programming languages with comprehensive libraries and tools for putting data science and machine learning into practice in an efficient manner. This unit will cover fundamental concepts and theories of data science and machine learning with focus on their practical use and implementations. The issue of machine bias in machine learning and how it may have an adverse impact on the common good will be examined. The aim of the unit is to learn both theoretical and practical data science and machine learning techniques to build real-world data science and machine learning solutions.
Cyber security is the practice of protecting networks, computer systems, and data from malicious attacks. With the increasing threats of data breach and leaks in our interconnected world, flntech companies, hospitals, government agencies, and every other sector are investing in cybersecurity infrastructure to protect their data and consumers from malicious attacks. However, there is a global shortage of cyber security experts and this number is growing every year. This unit is designed to help students develop a deeper understanding of modern information and cyber security challenges, mitigation techniques and tools. The unit demonstrates the basic cyber security concepts, security tools and the common architectures used as industry standards. Students will learn how to defend against cyber threats and attacks and study existing techniques for managing security issues and maintaining the working environment. The unit also covers ethical and legal issues in cyberspace to understand how cyber security affects legal compliance and solidarity in communities and society. The aim of this unit is to equip students with some background knowledge in cyber security, which scaffolds an advanced unit in network security.
Computer programs are widely used to drive practical business applications. As a result, global demand for people with programming skills is increasing. Programmers are commonly required to ethically maintain legacy code, to develop new applications to make business competitive and to improve software security. This unit introduces students to key concepts of computer program design and development using appropriate data structures, control structures and functions. In addition, students will learn object-oriented programming and basic testing and debugging skills. The aim of this unit is to introduce the basics of a modern programming language for building simple software applications involving objects and functional components. Hence by studying this unit students will be able to support the common good of mankind by overcoming chronic shortages of programmers to drive modern business applications.
With the increasing reliance on technology, it is becoming more and more essential to secure every aspect of online information and data. Therefore, network security is very critical for any organisation and is essential to protecting client data. This unit covers the advanced network security concepts that require to developing students’ knowledge and practical skills in digital communication and security. This advanced unit explores the theoretical foundations and current landscape of cryptography, covering essential concepts required to understand complex security challenges in networked environments. The unit contents include networking concepts, classical cipher design and analysis, key management, digital signatures and hash algorithms, wireless security, web security, email security and data stewardship. The unit also focuses on applications of network security tools to prevent or detect security attacks. The aim of this unit is to provide students with a good understanding of network security issues and the importance of data stewardship, as well as the knowledge and skills they need to plan, design or implement in order to secure a networked environment.
This is the first of two units (Parts A and B) extending across two semesters. Both units provide practical experience in designing, developing and evaluating a particular information technology project or in thoroughly investigating a particular area of information technology. The project is generally software-based, although sometimes it may involve investigation of an information system for a particular industry. It covers the whole system development lifecycle from requirements analysis through design to implementation and testing. The two units provide project management, communication and technical skills to prepare students for transition from study to professional practice in industry. Both units require students to integrate and consolidate knowledge, attitudes and capabilities acquired in other units of study. The project work will involve project management, documentation, presentation, and possibly coding. The focus of Part A is to provide students with fundamental project management, communication and technical skills in the context of a particular information technology project. It specifically covers the catholic social thought of subsidiarity in managing a team-based project. The project has both team and individual work elements. A team of students will work together on the project, while each team member, while also involved in overall team-oriented responsibilities, will contribute to their team by employing the specialist capabilities of their professional pathway.
This is the second of two units taken across two semesters, providing practical experience in designing, developing and evaluating an information technology project or investigating an IT area in depth. Projects are usually software-based and span the full system development lifecycle—from requirements analysis and design to implementation and testing. Together, Parts A and B develop project management, communication and technical skills to support students’ transition to professional practice. Students consolidate knowledge from prior units through project management, documentation, presentations and, where relevant, coding. Part A focuses on foundational project planning, communication and technical skills. Part B centres on implementing and testing the project according to the plans developed in Part A, applying software engineering principles. Students develop and test their system, designing test cases to evaluate functional and non-functional requirements. A final report is required, outlining project outcomes, challenges, performance analysis and recommendations for future improvement, including consideration of human dignity and diversity. The unit aims to equip students with essential project management and system development capabilities, enabling them to become responsible IT professionals who are prepared for industry and committed to working for the common good.
A solid foundation in several aspects of Mathematics, including logic and algebra, are a requirement of a variety of career-oriented degrees including Computer Sciences and all Initial Teacher Education (ITE) students studying to be secondary Mathematics teachers. In this unit, students are introduced to foundational concepts and structures of mathematics. Topics covered include matrices, graphs (networks), vectors, sets, functions, and complex numbers.  This unit also extends students’ understanding of number systems to include complex numbers. Numerous important real-world applications of mathematics are explored. The aim of this unit is to provide students with foundational knowledge of logic, algebra, and mathematical reasoning to support further study in Mathematics and Computer Sciences.
Calculus was developed to study quantities and processes that are continuously changing and so is crucial for modelling and understanding most physical processes. To support further development of more advanced mathematical skills, it is important that all students have a known and relatively advanced understanding of basic calculus. The study of calculus is fundamental in all Mathematics and is a requirement of a variety of career-oriented degrees including Computer Sciences and all Initial Teacher Education (ITE) Mathematics courses. This unit builds upon a basic knowledge of basic calculus obtained in high school to provide a solid base for further study by providing a brief review and extension of those concepts: functions, limits, continuity, differentiation and integration. It is accepted that students who have studied calculus at high school may have differing levels of knowledge. The aim of this unit is to consolidate and extend students’ knowledge and understanding and to ensure that students have, at minimum, a known level of competence with the basic ideas of calculus that may then be applied in later units.
This unit provides students with an ethical and practical approach to the analysis of business data uncertainty with emphasis on generating useful information for business and personal decision-making. It covers gathering and describing data, the role of probability in measuring uncertainty, statistical inference using various common parametric and non-parametric techniques and analysis of relationships between variables. A knowledge of Statistics is critical for many professions including economics, financial analysis, marketing, management and accounting. Numbers and figures are used every day in business to make predictions. If you invest in financial markets, statistics can be used to predict the price of a stock 12 months from now based on company performance measures and other economic factors both locally and globally. This is just one example that illustrates how statistics are used in our modern society. Students will be able to apply data analysis tools with a focus on the application of those tools to understand the issues of vulnerable populations. The unit provides students with the necessary knowledge and skills needed to apply data analysis techniques for business decision making.

Community engagement unit (10CP)

Credit points

Computer Science professionals need to apply and communicate discipline specific knowledge and skills to a demographically broad audience. Crucial to the development of these skills is the opportunity to collaborate with individuals and groups whose worldviews may be different from their own. A computer science community engagement (CE) experience is a transformational learning opportunity. It exposes students to new perspectives, challenging them to gain an expanded and enhanced understanding of their community and the people within it. This drives the development of key qualities, such as empathy. In this unit, students will engage with communities experiencing disadvantage or marginalisation, through working with social enterprises, not for profit organisations, individuals within the University, and incorporated community groups. These qualities and skills will be developed by engagement with a partner community to identify knowledge requirements, prepare and plan a community engagement experience, and critically reflect on the learning from the experience. The aim of this unit is to foster knowledge and understanding of community engagement while applying ethical, personal communication and professional skills.

Core curriculum units (20CP)

Credit points

This unit, available within ACU’s Core Curriculum, introduces students to some key tools for assessing information, and reasoning and communicating clearly, skills that are of real-world value for all areas of personal and professional life. Students will learn to structure arguments clearly for different audiences; to evaluate evidence and testimony; to engage constructively in cases of disagreement; to identify and guard against characteristic forms of bias and error; and to present oral and written presentations persuasively. Intellectual virtues like clarity, openness and charity are emphasised. The study of reasoning and argumentation has long been at the centre of the Catholic intellectual tradition in its inheritance from the medieval monastic tradition that itself preserved and developed ancient Greek logic and rhetoric. It remains a central dimension of contemporary Catholic thought in its focus on the togetherness of faith and reason in the pursuit of the common good. As such, students in this unit engage with each other on a diverse range of urgent contemporary issues, practicing skills in listening to others, crafting arguments, and conveying views effectively. Set in the context of this social media age, the unit aims to prepare students to be reflective, creative, responsible citizens and effective communicators in diverse domains of life.
The unit aims to develop students’ critical understandings of the origins, nature and roles of the sciences, their relation to philosophical and theological reflection, and the implications of the sciences for our understanding of human dignity, the integrity of creation, and the common good. The revolutions in scientific understanding of the last 500 years have changed how see our earthly home, from the physical centre of creation to a tiny planet suspended within an unimaginably vast universe. The biological sciences have changed the way we understand the human body, its processes, and its relation to other living things. But today’s sciences have developed in complex historical interactions with the Abrahamic faith traditions and wider social and cultural changes, in ways that are often overlooked or misunderstood, but which this unit will lead students to examine. Building on critical understandings of the origins of today’s sciences, students will undertake case studies concerning contemporary social and ethical challenges and opportunities connected to scientific research and technology. Responding to a world where the authority of the sciences is increasingly contested, this unit aims to prepare students to critically engage with community and contribute to ongoing debates around issues in science and technology.

Elective units (40CP)

Credit points

Without knowledge of ethical accounting and financial analysis skills the business world could collapse. This unit will provide a non-specialist grounding in accounting and financial management so that students can appreciate the financial dimensions of decisions within business. Moreover, the unit considers corporate social responsibility within the context of financial management and sustainability in the promotion of stewardship for social good. The unit will enable students to understand the impact of economic transactions on a business’ financial and operating capability as well as to recognise the use of accounting information in decision making without getting bogged down in the mechanics of the system. Building on this, students will develop fundamental financial planning and forecasting skills so that students can utilise these skills in life or business. This unit aims to introduce accounting and financial management skills in a non-technical way so students will be able to develop financial and accounting literacy as a life skill.

Anyone working in, or with, business will interact with organisational systems and the people within them. Understanding the characteristics of how people and organisations work, and are practically navigated, is an important part of any business practitioners’ role. This unit provides introductory information about these issues including basic management theory and practice, systems thinking and management, organisational structures, organisational communication, teams and leadership. It also introduces students to disciplines important in managing people in organisations, namely management and human resource management.
The unit incorporates the values of global social responsibility. The unit will develop the capabilities of students to be future generators of sustainable value for business and society at large and to work towards an inclusive and sustainable global economy.
Students will have the opportunity to apply basic management models and concepts to organisational problems including international and indigenous perspectives.
The aim of this unit is to provide students with a broad foundational base for those working with people and systems in organisations.

This unit is the foundation for understanding the legal framework that governs commercial activity and business decision making. The aim of the unit is to equip students with the core principles of business law as they apply to setting up and operating a business and conducting commercial transactions. Students will examine the nature and formation of contracts, enforceability, breach and remedies, and the legal rights and obligations of parties to commercial arrangements. They will also develop a basic knowledge of property law principles, particularly the transfer of title in the sale of goods and the legal implications of ownership, possession, and risk. The unit applies these principles to two fundamental commercial activities: establishing a business structure and entering into day-to-day commercial transactions. Students will further develop skills in identifying legal issues, interpreting simple legal documents, and applying legal principles to practical business scenarios.
As software systems become increasingly complex and interactive, a deeper understanding of advanced programming concepts is essential for students aiming to build robust, user-friendly, and data-driven applications. This unit builds on the foundational knowledge and guides students toward the development of more specialised graphical user interface (GUI) based software applications. Core topics include event-driven programming, GUI design, file input/output operations, data structures, and generics. Through practical programming tasks, students will have the opportunity to gain the skills to address real-world problems that require effective user interaction and data handling. These skills are extended to complex, real-world application development. The unit also emphasises the importance of responsible and efficient computing, promoting energy-conscious development practices that contribute to long-term sustainability in software design.
Work Integrated learning (WIL) is the term used to describe learning activities that allow students to apply their academic learning in a ‘real-life’ environment provided by a real industry partner or a University organisation working on a real project. WIL strengthens students’ essential job-ready skills and experiences and provide students with the opportunity to learn about workplace culture, prepare for the future world of work, develop professional networks and build their employability skills. WIL may be conducted on or off campus, face-to-face or online, and paid or unpaid. Each student is jointly supervised by an academic supervisor and a placement supervisor. The aim of this unit is to enhance students’ professional knowledge, apply theory, practices and technical skills, and to develop their understanding of organisational and business culture and processes. Students will gain the confidence, knowledge and skills necessary to effectively prepare for a future career in the IT industry. Through work integrated learning, students will also get a clear understanding of the impact of IT on workers and working conditions.
Artificial intelligence (AI) is the intelligence demonstrated by machines, devices, agents or computer programs, in addition to the natural intelligence displayed by humans and animals. AI is often considered as the study of intelligent and rational agents or machines that mimic cognitive functions associated with the human mind, such as problem solving, reasoning, planning, learning, actioning and decision making. Machine learning is a subfield of AI that studies the ability to improve machine performance based on experience. Machine learning (ML) employs algorithms and mathematical models that computer systems use to make decisions or predictions and it is prevalent in many contemporary AI applications that make common good and build better stewardship ranging from microelectronic devices to online services benefiting billions of users. This unit will cover essential aspects of AI and ML, both theoretically and practically. This includes understanding, design and implementation of fundamental problem-solving algorithms in AI such as heuristic search and game theory as well as supervised and unsupervised ML algorithms. The aim of the unit is to learn essential concepts and techniques of AI and ML towards designing and building AI-enabled applications that makes people’s lives better.

Data Science specified units (80CP)

Credit points

To make data meaningful and informative, it must be transformed from raw and often messy formats into structured, reliable, and analysable forms.

This unit introduces the end-to-end process of data wrangling, which includes data discovery, cleaning, transformation, integration, and validation to prepare data for analysis and modelling. Students will also explore the fundamentals of machine learning, including how prepared data is used to build and evaluate simple predictive models. By combining data preparation with introductory modelling, students will learn to generate insights that support data-driven decision-making in real-world contexts across business and community sectors.

The aim of this unit is to equip students with the practical and conceptual skills to prepare, analyse, and model data for meaningful insights.

To effectively work with datasets, data scientists need be able to apply established techniques of statistical analysis to the information they work with. Statistical modelling is the application of statistical analysis techniques to datasets. It is a mathematical representation of observed data, allowing relationships between data to be identified, predictions about future sets of data made, and visualization of data to aid understanding. Statistical modelling techniques fall into two groups; supervised learning includes regression and classification models; unsupervised learning includes clustering algorithms and association rules. By exploring case studies and industry-relevant examples, students will have the opportunity of gaining an in-depth understanding of the range and application of both supervised and unsupervised statistical data modelling techniques.

The aim of this unit is to facilitate the development of skills required to analyse datasets.

The ability to anticipate outcomes and make data-driven decisions is fundamental to success across industries. Predictive modelling and analytics leverage historical and current data through statistical, machine learning, and deep learning techniques to estimate future behaviour, identify patterns, and inform strategic decisions.

In this unit, students will explore predictive approaches across diverse data types and apply appropriate techniques to solve real-world problems. The unit emphasises reproducible modelling practices, feature engineering, model evaluation, and the communication of analytical results to stakeholders. Students will develop both technical proficiency and critical insight into the opportunities, limitations, and ethical considerations of predictive analytics in practice.

The aim of this unit is to equip students with the knowledge and practical skills to design, implement, and communicate predictive models that support informed decision-making and innovation across a range of domains.

In an era where technology drives innovation and transformation, computing professionals must be able to design and manage evidence-based projects that address real-world challenges and enable sustainable growth and agility in organisations.

This unit serves as the first stage of a two-part capstone sequence designed to foster independent inquiry, applied research, and problem-based learning. Students will engage with the relevant research literature, identify an area of investigation, and complete the exploratory and planning phases of a research or industry-aligned project. Drawing on knowledge and skills developed throughout their studies, students will integrate technical, analytical, and ethical perspectives to define a research problem, formulate appropriate methodologies, and prepare a structured plan for project implementation in the subsequent capstone unit.

The aim of this unit is to equip students with the knowledge, critical thinking skills, and research capability required to undertake and plan a substantial, inquiry-based project within their discipline of study—whether in data science, artificial intelligence, or a related computing field.

In an era where technology enables continuous innovation, computing professionals must be able to design, implement, and evaluate evidence-based projects that generate meaningful insights and drive positive change in organisations and communities. This unit serves as the second stage of a two-part capstone sequence, building on the work undertaken in Project A: Research Essentials. Both units are designed to foster problem-based, self-directed learning and applied research capability.

In this unit, students apply the knowledge and skills developed throughout their studies to implement, evaluate, and communicate a research or industry-aligned project. They will employ a combination of theoretical, analytical, and computational methods to develop and test models, analyse data, and interpret findings in response to their defined research objectives or hypotheses.

The unit culminates in the submission of a comprehensive project report and presentation, demonstrating the student’s ability to deliver a technically sound, ethically responsible, and professionally communicated solution.

The aim of this unit is to enable students to implement, evaluate, and communicate an advanced research or applied computing project, integrating technical expertise, analytical reasoning, and professional practice.

The explosion in data and digital technologies has opened new ways of obtaining data-driven insights. Organisations increasingly require professionals who can work with modern data ecosystems, streaming data sources, and visualisation tools to extract, analyse, and communicate insights.

This unit introduces advanced techniques in data analytics, including big data processing and visualisation using industry-standard and open-source tools. Students will use platforms such as Power BI, Google Looker Studio, Tableau, and Python-based libraries and big data technologies (e.g., Hadoop, Spark, cloud-native platforms) to transform raw data into meaningful insights. Students will also explore data ethics, geospatial analysis, and advanced dashboarding techniques.

The aim of this unit is to equip students with job-ready skills in applied analytics, big data techniques, data storytelling, and dynamic reporting—enabling them to deliver strategic, ethical, and environmentally responsible decisions in complex real-world scenarios.

Deep learning drives many real-world AI applications, including computer vision, natural language processing, and large language models (LLMs), and is a core approach within modern artificial intelligence (AI). Graduates, therefore, need the capability to design AI projects responsibly, select appropriate methods, and evaluate solutions that are effective, safe, and aligned with the common good.

This unit develops conceptual and practical skills in contemporary AI, with a strong emphasis on deep learning. Students begin with a recap of core machine learning concepts, then progress to designing and developing deep learning models and exploring other emerging AI technologies. They will work through the full model lifecycle, including development, training, inference, testing, and evaluation. Using tools such as Python and Keras, students implement and assess AI solutions across key areas, including computer vision, natural language processing, large language models (LLMs), anomaly detection, and reinforcement learning. The unit also integrates Microsoft Azure AI Fundamentals to familiarise students with industry standards, design principles, and common AI solution patterns. Throughout, students examine foundational AI use cases that promote stewardship and the common good, with sustained attention to ethics, safety, and human dignity.

This unit aims to equip students with advanced AI knowledge and skills to design, develop, and evaluate AI-enabled applications responsibly, promoting the common good and upholding human dignity.

Organisations today face the challenge and opportunity of leveraging vast amounts of data to derive actionable insights. Data mining is a critical process for discovering patterns, relationships, and trends within large and complex datasets to support strategic and operational decision-making.

This unit builds on foundational studies in data science and programming, and provides a comprehensive exploration of the knowledge discovery process, incorporating essential topics such as data pre-processing, classification, clustering, association rule mining, anomaly detection, sentiment analysis, and sequential pattern mining. Emphasis is placed on applying both descriptive and predictive data mining techniques to solve real-world problems, using visual data mining tools (e.g. RapidMiner and Orange) and Python programming.

Case studies and applied projects will help students design, implement, and evaluate end-to-end data mining workflows, applying ethical principles and critically reflecting on issues of data privacy, bias, and explainability.

The primary aim of this unit is to develop industry-ready professionals capable of applying data mining techniques and tools to support informed and ethical decision-making across diverse domains.

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