FIT3208 · Artificial intelligence in practice: Project 1

Overview

This unit is the third stage of the Artificial Intelligence practice program. You will continue working within a student-led company, contributing to real projects, products or services that involve the responsible application of artificial intelligence. Building on earlier practice units, you will move from guided contribution toward greater independence, taking responsibility for more substantial work while continuing to operate within team, project and company expectations. At this stage, you will also help sustain the company as an ongoing learning and working environment. This includes contributing to the recruitment, selection and onboarding of students entering the first practice unit by helping define role needs, supporting application or interview processes, and assisting new students to understand company expectations, workflows and professional practice. You will take greater agency over your professional and academic development by identifying the AI capabilities, professional practices and evidence you want to develop. In consultation with mentors, peers and company leaders, you will set development goals, seek feedback, and build portfolio evidence of your growth. Your work will involve selecting and applying AI methods, tools and development workflows in authentic contexts, while considering limitations, risks, evidence, impacts and responsible use. Assessment is centred on an individual evidence-based portfolio demonstrating your contribution to company work, your support for new students, your response to feedback, and your advancing AI capability. This unit prepares you for the capstone practice unit, where you will be expected to demonstrate more independent and integrated application of AI capability in professional contexts.

Offerings

The Handbook publishes no offerings for this unit.

Assessment

The Handbook publishes no assessment items for this unit yet.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Direct your professional and academic development by identifying capability goals, seeking and responding to feedback, supporting recruitment and onboarding activities, and evidencing growth through reflective practice;
2. Select, apply and evaluate artificial intelligence methods, tools and workflows in a company project context, explaining their suitability, constraints, limitations and responsible use;
3. Contribute to the design, development and evaluation of AI-enabled applications, components or workflows that respond to real project needs and stakeholder contexts;
4. Demonstrate advancing Artificial Intelligence course capability through portfolio evidence of individual contribution, technical decision-making, responsible practice, feedback response and professional judgement.

Workload

No workload detail published.

Student experience, not official rules. Nothing here changes what the Handbook says.