Overview
In this unit, you will study advanced artificial intelligence technologies that drive modern intelligent systems. You will examine the theoretical foundations alongside the practical development of research‑informed AI models, with a focus on how such models learn from large and complex datasets. Through practical design and implementation activities, you will integrate disciplinary knowledge with contemporary research to create effective AI solutions. You will critically evaluate the ethical, social, and professional issues surrounding AI deployment. You will also develop the capability to communicate complex AI concepts, design rationales, implementation choices, and evaluation findings to both expert and general audiences using professional standards.
Details
Pre-requisites or Co-requisites
Pre-requisite: COIT20277 Introduction to Artificial Intelligence. Co-requisite: STAT20029 Statistics for Managerial Decisions.
Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).
Offerings For Term 3 - 2027
Attendance Requirements
All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Academic Progression Policy and Procedure
- Student Refund and Credit Balance Policy and Procedure
- Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Feedback from Student Feedback
Students would like the tutorial to include a quick debrief using real-world scenarios or analogies to make it easier to digest and understand.
In the next offering, the unit will add examples to the weekly tutorial questions that reflect real-world scenarios, helping students better understand the unit's key concepts.
Feedback from Self-Reflection
It is increasingly necessary to include large language models (LLMs) as a dedicated weekly lecture topic in the course, as they have become a foundational technology across modern software development, data science, and artificial intelligence applications.
The lecture slides introducing LLMs should be revised to better explain how contemporary AI systems generate, reason with, and adapt language-based knowledge in real-world contexts. The lecture should emphasise intuitive explanations, visual system diagrams, and concrete use cases, complemented by simplified examples and demonstrations.