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Unit outline_

DECO3000: Designing Intelligent Systems

Semester 2, 2024 [Normal day] - Camperdown/Darlington, Sydney

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 and comfort coding in JavaScript (definitely) and Python (preferably)

Available to study abroad and exchange students

No

Teaching staff

Coordinator Kazjon Grace, kazjon.grace@sydney.edu.au
Tutor(s) Alton Ong, aong3299@uni.sydney.edu.au
The census date for this unit availability is 2 September 2024
Type Description Weight Due Length
Assignment group assignment Final Project Submission
A working AI-powered prototype, with documentation.
30% Please select a valid week from the list below
Due date: 31 Oct 2024 at 23:59
N/A
Outcomes assessed: LO1 LO2 LO3
Assignment An AI-Assisted Essay On AI
Write an essay on a topic related to AI, using an AI writing tool to draft.
25% Week 05
Due date: 29 Aug 2024 at 23:59
1000wds
Outcomes assessed: LO1
Presentation AI Project Concept Pitch
Present a project pitch for your final assignment (individually)
25% Week 09
Due date: 26 Sep 2024 at 23:59
5 mins presentation, plus 5 mins Q&A.
Outcomes assessed: LO1 LO3
Presentation group assignment Project Proof-of-Concept Presentation
Show working core functionality for your final project (in your pairs).
20% Week 12
Due date: 24 Oct 2024 at 23:59
10 minutes for both demo a critique/Q&A.
Outcomes assessed: LO2
group assignment = group assignment ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

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.

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, calculated multiplicatively (i.e. if you are late by three days, your mark will be multiplied by 0.85). 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 Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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 2023 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 2023. 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

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) LO1 LO2 LO3

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 any class (lecture, or tutorial) across more than two weeks, your overall grade for this unit will be penalised by 5% 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, or other personal circumstances, but not (also for example) conducting 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 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.

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

  • LO1. Evaluate proposed use cases for AI for plausibility and complexity, as well as design plausible conceptual architectures for provided AI use cases.
  • LO2. Prototype 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

This unit was offered for the first time last year, and feedback was very positive. For this year we're mainly focused on updating the tech being taught in the tutorials to keep up with this fast-moving field.

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 platform) may be necessary. Total costs for this unit should not exceed about $25-50, and in many cases will be <$10.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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