Outline

Overview

This unit of study will equip students with the capacity to design interactive systems with an artificial intelligence (AI) component. From our commute to our kitchens, intelligent systems are shaping how we live. Our entertainment is handpicked by machines, our homes are connected to smart devices that wait on our every need, and our roads may soon be dominated by high-speed robots. In this unit students will gain a practical understanding of what AI is and isn't capable of, through a combination of case studies and problem-solving. Students will develop real prototype AI-driven interactive systems, exploring possible futures of these technologies and how they might reshape daily life.

Unit details and rules

Academic unit	Design Lab
Credit points	6
Prerequisites ?	DECO2017 and (DECO3100 or DECO3200 or DECO4200)
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Experience programming (in any language)
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Kazjon Grace, kazjon.grace@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written work	An AI-Assisted Essay On AI Revise and improve an AI-drafted essay on a provided AI topic.	25%	Week 05 Due date: 04 Sep 2025 at 23:59	1000wds	AI allowed
Outcomes assessed:
Presentation	AI Project Concept Pitch Present a project pitch for your final assignment (individually)	25%	Week 09 Due date: 09 Oct 2025 at 23:59	5 mins presentation, plus 5 mins Q&A.	AI allowed
Outcomes assessed:
Presentation	Project Proof-of-Concept Presentation Show working core functionality for your final project (in your pairs).	25%	Week 12 Due date: 30 Oct 2025 at 23:59	10 minutes for demo and critique/Q&A.	AI allowed
Outcomes assessed:
Creative work	Final Project Submission A working AI-powered prototype, with documentation.	25%	Week 13 Due date: 06 Nov 2025 at 23:59	N/A	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Detailed information for each assessment can be found on Canvas. Lack of attendance can also lead to grade penalties, details of which can be found in "Attendance and Class Requirements" below.

Assessment criteria

Result name	Mark range	Description
High distinction	85 - 100	Work of outstanding quality, demonstrating mastery of the learning outcomes assessed. The work shows significant innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or exceptional skill.
Distinction	75 - 84	Work of excellent quality, demonstrating a sound grasp of the learning outcomes assessed. The work shows innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or superior skill.
Credit	65 - 74	Work of good quality, demonstrating more than satisfactory achievement of the learning outcomes assessed, or work of excellent quality for a majority of the learning outcomes assessed.
Pass	50 - 64	Work demonstrating satisfactory achievement of the learning outcomes assessed.
Fail	0 - 49	Work that does not demonstrate satisfactory achievement of one or more of the learning outcomes assessed.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late work will receive a 5% per calendar day penalty, (i.e. if you are late by three days, 15 marks out of the 100 total will be subtracted). Teaching staff cannot guarantee availability every day for late presentations, and penalties will accrue even when the delay is due to the staff member's schedule.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity	Learning outcomes
Weekly	Lectures, in-class discussion and guided tutorial exercises on AI, interacting with AI, and how to design intelligent systems.	Lecture and tutorial (3 hr)

Attendance and class requirements

Attendance in this unit is mandatory, and unexplained absences will result in penalties to your final grade. Specifically, if you miss more than one class and do not provide an explanation, your overall grade for this unit will be penalised by 3% per additional unexplained absence.

Absences may be explained by emailing your tutor with a valid reason for your non-attendance, which includes illness, caring responsibilities, misadventure, unexpected work requirements, or other personal circumstances, but not conducting regular paid work.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

A list of required readings for this unit can be found on Canvas.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Evaluate proposed use cases for AI for plausibility and complexity.
LO2. Conceptualise and prototype plausible conceptual architectures for provided AI use cases, based on both predictive and generative machine learning solutions.
LO3. Design interfaces for interacting with intelligent systems, with attention to both the user experience/interaction design dimension as well as the architecture (inputs, model, outputs) of the intelligent system itself.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Updates this year focus on staying ahead of the rapidly-changing field of AI.

Additional information

Additional costs

To use some of the AI platforms being taught in this unit and necessary for some projects, a small credit card payment (to the provider) may be necessary. Total costs for this unit should be in the range of $25-100.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Disclaimer

On this page

Useful links

DECO3000: Designing Intelligent Systems

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Disclaimer

On this page

Useful links