FIT3209 Artificial intelligence in practice: Project 2
Faculty of Information Technology
FIT3209 Artificial intelligence in practice: Project 2 is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology. It isn't offered in 2027. It needs FIT3208 and unlocks 1 unit, leading on to 2 units in all.
- Credit points
- 6
- Offered in 2027
- Not offered
Reviews
No reviews yetNo reviews yet. Be the first to review FIT3209.
Requisites
Before FIT3209
Prerequisites
Pass these before you enrol.
After FIT3209
1 unit list FIT3209 as a prerequisite or corequisite.
Overview
This unit is the capstone unit in the Artificial Intelligence practice stream and, for most students, the final stage of the Monash IT Industry Practice Program. You will make a substantial individual contribution to a student-led company through real projects, products or services involving the responsible application of artificial intelligence.
At this stage, you are expected to operate with professional independence, contribute to company direction and outcomes, and demonstrate readiness for industry or further study. You will take responsibility for your own professional and academic development, shape the evidence you need to demonstrate capability, and contribute to the sustainability of the company through technical contribution, mentoring, process improvement, project delivery, stakeholder engagement or leadership.
As this unit is an exit point from the practice stream for most students, you will also help ensure that the company is well positioned to continue progressing the AI-enabled work you have been engaged with. This may include documenting decisions, improving workflows, preparing handover materials, supporting continuity of project knowledge, mentoring successors, strengthening team practices, and identifying next steps for the company’s products, services or projects.
You will prepare a showcase portfolio that presents evidence of your capability, achievements, professional growth and individual contribution. This portfolio will support reflection on your development across the practice program and provide a curated record of your work that can be used when applying for industry roles, placements, graduate opportunities or future study.
Your work will require you to apply artificial intelligence methods, tools and development practices with judgement, while considering security, privacy, ethics, social impact, project constraints, data needs, stakeholder expectations and the limitations of AI-enabled systems.
Offerings in 2027
The 2027 handbook lists no offerings for FIT3209.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Apply responsible AI and computing practices by addressing security, privacy, ethical, social good, accessibility, sustainability and stakeholder impact considerations in company project work;
- 2
Direct your professional and academic development through self-assessment, targeted development planning, feedback response and evidence-based reflection, preparing a showcase portfolio that communicates your capability, achievements and readiness for industry or further study;
- 3
Communicate AI concepts, technical decisions, progress, risks, evidence and outcomes clearly to technical and non-technical stakeholders using appropriate professional forms;
- 4
Plan, coordinate and sustain company project work by managing tasks, risks, dependencies, quality expectations and handover processes, collaborating across teams to position products, services or projects for continued progress beyond your contribution;
- 5
Investigate complex AI-related problems, evaluate alternative approaches and justify defensible solutions using evidence, experimentation and professional judgement;
- 6
Apply AI-enabled digital, data, programming and design practices to develop, adapt, test, document and evaluate AI-enabled system elements, workflows or components that meet stakeholder needs and project constraints;
- 7
Select, apply and critically evaluate AI methods, tools, workflows and development practices to design, develop and evaluate AI-enabled applications or components in authentic professional contexts.
Common questions
More details
- Credit points
- 6
- Level
- 3
- Study level
- Undergraduate
- Faculty
- Faculty of Information Technology
- Type
- Coursework
- EFTSL
- 0.125
- Student contribution
- SCA Band 2
- Study abroad
- Available
- Handbook years
- 2027