Generative AI Model Applications Development

In this unit, you will learn how to design and build real-world applications powered by Generative AI models, moving beyond experimentation to professional, deployable solutions. Generative AI—especially large language models—can create text, code and structured outputs, but effective use in practice requires careful engineering to achieve reliability, safety and value in specific contexts.

You will develop the skills to frame a problem, select an appropriate GenAI approach, and prototype solutions that integrate with data sources and external tools. You will learn how to improve quality through structured prompting, retrieval-based techniques, evaluation and testing, and you will apply safeguards to manage common risks such as hallucinations, bias, privacy and security concerns.


Learning is hands-on and studio-based. You will work through authentic scenarios and build working prototypes, supported by guided workshops, practical labs, and rapid feedback cycles. By the end of the unit, you will be able to develop and justify a GenAI application design, implement a functional prototype, and evaluate its performance and responsible use in a professional setting.

Learning Outcomes

On successful completion of this unit, students will be able to:

1. Analyse and formulate Generative AI application requirements and solution approaches for complex, real-world scenarios.
2. Design and implement GenAI-enabled application architectures and prototypes that integrate models with organisational data sources and external tools/services.
3. Synthesise prompt and workflow strategies, including structured outputs, retrieval-supported generation, tool use, to improve reliability, usefulness and user experience.
4. Critically evaluate GenAI application performance using appropriate evaluation methods and evidence, and refine solutions based on testing outcomes and stakeholder needs.
5. Critique ethical, legal, privacy, security, bias, cultural and Indigenous data governance risks in GenAI applications, and justify safeguards and responsible deployment decisions.