Bachelor of Computing, role specialisation in Artificial Intelligence Engineer
Artificial Intelligence Engineers develop, build and support intelligent systems that leverage machine learning, data analytics, and automation to solve complex problems.
Students may graduate with a Role Specialisation recorded on their academic transcript, reflecting their chosen career pathway and demonstrated competencies.
Specialisation Overview
Artificial Intelligence Engineers design algorithms, build predictive models, and develop, deploy, and support AI technologies and solutions across industries such as healthcare, finance, and technology.
Learning Outcomes
Students undertaking this role specialisation will:
Develop and implement machine learning and AI models
Analyse, clean, and preprocess large datasets for model development
Apply statistical, mathematical, and algorithmic techniques to solve real-world problems
Build predictive and data-driven solutions for business and industry applications
Evaluate and optimise model performance using validation and tuning techniques
Deploy AI models into production environments
Apply ethical and responsible AI practices, including bias mitigation and data privacy
Communicate AI insights to both technical and non-technical stakeholders
Australian Computer Society (ACS)
- Industry events and networking opportunities
- Career resources and professional development
- Webinars, technical content, and learning resources
- Access to the ACS member community
Industry Alignment
This role aligns with the following ANZSCO classifications:
Analyst Programmer
(261311)
Developer Programmer
(261312)
Software Engineer
(261313)
DevOps Engineer
(261316)
Software and Applications Programmers
(261399)
Course Structure
The Bachelor of Computing is an innovative three-year (144 credit point) degree comprising three integrated streams that run in parallel throughout the program. Clear integration points exist between and across all streams, ensuring theory is consistently applied in practice.
Core Units Stream (72 credit points)
This stream provides the core conceptual knowledge required for the degree and ensures all students develop the fundamental skills expected of computing graduates.
Students complete 18 core units (4cp each) across the program, covering foundational computing, programming, systems, software engineering, cybersecurity, and emerging technologies.
Simulated Consultancy Stream (36 credit points)
This stream embeds students in a simulated professional IT consulting company throughout the degree.
Students progress through a structured sequence of roles:
Intern
Junior Consultant
Senior Consultant
Across each stage, students work on real-world consultancy projects, which—where possible—are sourced from industry clients. Projects require students to integrate theoretical knowledge from core units and apply it to practical, real-world problems.
Consultancy project work is supported by workshops and seminars focused on developing additional professional and workplace capabilities.
Career Pathways Stream (36 credit points)
The Career Pathways stream allows students to customise their degree while building industry-relevant knowledge and capabilities.
Modules in this stream are designed to:
Evolve rapidly
Reflect current industry practices and emerging technologies
Support specialisation in specific career areas
Students may also choose to undertake one or more industry certifications as part of this stream.
Role Specialisation
Students may graduate with a Role Specialisation recorded on their academic transcript.
This is achieved by demonstrating a defined set of competencies aligned to a specific industry role—such as:
Systems Analyst
DevOps Engineer
UX Designer
Competencies are developed and evidenced through targeted content in both the Simulated Consultancy and Career Pathways streams.
This provides employers with a clear, role-specific understanding of a graduate’s skills, experience, and workplace readiness.
More Information
Requirements
To graduate with this role specialisation, students must complete:
- Completion of Artificial Intelligence and Machine Learning (COM322)
- Completion of at least 100 hours of simulated consultancy work
- Must demonstrate at least 6 out of 8 learning outcomes
- Completion of 500 hours of career pathways modules
- Up to 100 hours: foundational knowledge
- Minimum 400 hours: specialist AI engineering skills
- Includes at least one industry certification (e.g. AI-related certification)
Assessment of Outcomes
Students must:
- Complete 100 hours of simulated consultancy work on AI-related projects
- Demonstrate learning outcomes through their e-portfolio
- Successfully claim at least 4 SFIA skills
Assessment requirements include:
- At least 2 skills at SFIA Level 3 (Apply) or higher
- Remaining skills at SFIA Level 2 (Assist)
SFIA Skills Framework
Governance, Risk & Compliance
- AI and Data Ethics (AIDE)
Change & Transformation
- Business Situation Analysis (BUSA)
- Feasibility Assessment (FEAS)
- Business Process Improvement (BPRE)
- Business Modelling (BSMO)
Data & Analytics
- Data Modelling and Design (DTAN)
- Data Analytics (DAAN)
- Machine Learning (MLNG)
- Business Intelligence (BINT)
- Data Engineering (DENG)
Entry Requirements
Admission to the Bachelor of Computing is based on applicants meeting the academic and English language requirements outlined below. All applications are assessed in line with SPI’s admissions policies and procedures.
Academic Requirements
Applicants must have completed one of the following:
Australian Year 12 (NSW HSC or equivalent national or international qualification); or
A Certificate IV (AQF Level 4) qualification or higher.
Applicants are expected to have studied Mathematics at a level equivalent to NSW HSC Mathematics (2 Unit)
English Language Proficiency
English as a First Language – Applicants must hold citizenship or long-term residency (minimum of 10 years) in an English-speaking country recognised by SPI and have completed secondary or higher education in that country.
English Not as a First Language – Applicants are required to provide a valid English proficiency certificate as proof of English language competency.
Academic Requirements
International applicants must have completed:
A secondary education qualification equivalent to Australian Year 12, or
A Certificate IV (AQF Level 4) qualification or higher.
Applicants are expected to have studied Mathematics at a level equivalent to NSW HSC Mathematics (2 Unit)
Additional Information
Applicants must be at least 18 years old at course commencement.
Admission is subject to assessment and meeting all entry requirements does not guarantee an offer.
Applicants who do not meet standard requirements may be considered under Special Consideration, subject to approval by the Academic Dean
English Language Proficiency
International applicants must meet one of the following English language requirements:
English Language Test Results
IELTS (Academic): Overall 6.5, with no band less than 6.0
PTE Academic: Overall 58, with no sub-score less than 50
TOEFL iBT: Overall 79, including minimum scores in each skill area
TOEFL PBT: Overall 550, including Writing 4.5
English test results must be valid and taken within three years prior to course commencement
For full admissions requirements please read the Student Admissions and Enrolment Policy and Bachelor of Computing Admissions Criteria. For SPI Inherent Course Requirements, please refer to the SPI Inherent Course Requirements.
How to Apply
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