Course coordinator
Dr Shakes Chandra
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
The concept of computation is one of the central ideas in computer science and the basis of a few theories that attempt to explain everything in our universe. In this course, we will explore why the current generation of computing hardware is designed the way it is, the constraints it imposes on artificial intelligence based on this hardware and show that computation is possible outside the natural realm of computers we have today. The course will introduce the grand unified theory of computation based on Turing machines, Lambda calculus and cellular automation. It will present the Church-Turing thesis to show that all these models are all equivalent. The theory of computation based on Turing machines will also include an introduction to finite state machines and their role in constructing regular languages. The course will also briefly introduce quantum computation and its applications. The necessary mathematical preliminaries in will be covered during the course.
In this course we will explore:
- The role of artificial intelligence in computation and whetherﾠit is possible from our current model of computation
- Why the current generation of computing hardware is designed the way it is
- Why is computation necessary and what role it plays in science in general
- Show that computation is possible outside the natural realm of computers we have today.
- How computers of the future might be designed
Over the last few offerings of the course, we have reduced the number of modules to ensure that we cover the main concepts in more depth and provide a more practical perspective as well. We have also updated the content to be in more keeping with modern computer science and latest developments in artificial intelligence (AI).
Course requirements
Assumed background
This course assumes that students have some basic knowledge of Python programming. An introductory practical is provided in the first week as a refresher for students.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
MATH1061 and (CSSE1001 or ENGG1001)
Course contact
Course staff
Lecturer
Dr Shakes Chandra
Dr Kasra Khosoussi
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Lectures run all weeks from Week 1 to Week 13. Both Contacts and Practicals will be running each week, but only from week 2 to week 13 (inclusive).
Aims and outcomes
The aim of this course is to provide a modern overview of computational theory and computer science by:
- Presenting the main models of computation: Turing machines and Lambda calculus.
- Providing practical and theoretical groundings of these models and their relation to the Church-Turing thesis.
- Providing hands-on experience with theoretical computer science
- Introducing the emerging area of quantum computation.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Describe computation and its mathematical origins
LO2.
Explain decidability and universality associated with computation
LO3.
Demonstrate how to design finite state machines and regular languages
LO4.
Explain the role and implications of Turing machines and demonstrate how to design them
LO5.
Demonstrate understanding of Lambda calculus and its use in modern computer programming
LO6.
Appreciate the implications of the Church-Turing thesis
LO7.
Demonstrate a high level understanding of cellular automation and chaotic systems
LO8.
Recognise modern computational theories, such as quantum computation, and their advantages.
LO9.
Appreciate the role and implications of computation and computer science in society, industry and research.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Practical/ Demonstration |
Code Breaking Laboratory
|
20% |
17/03/2025 - 4/04/2025
Conducted in Allocated Prac |
| Practical/ Demonstration |
Cellular Machines
|
20% |
14/04/2025 - 2/05/2025
Conducted in Allocated Prac |
| Practical/ Demonstration |
Computational Models
|
20% |
19/05/2025 - 30/05/2025
Conducted in Allocated Prac |
| Examination |
Final Examination
|
40% |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Code Breaking Laboratory
- Hurdle
- In-person
- Mode
- Activity/ Performance
- Category
- Practical/ Demonstration
- Weight
- 20%
- Due date
17/03/2025 - 4/04/2025
Conducted in Allocated Prac
- Learning outcomes
- L01, L04
Task description
Demonstration of the Code Breaking lab in prac sessions.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
There are grade hurdles associated with this practical. See Course grading section.Submission guidelines
Lab sheet requirements are demonstrated to the teaching team during your allocated practical session.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Prac demos are completed as part of a scheduled prac class.
If there are exceptional circumstances, an exemption may be approved and may involve submitting/discussing your work as it stands. Exemptions must be requested as an extension with a note specifying exemption via my.UQ.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Cellular Machines
- Hurdle
- In-person
- Mode
- Activity/ Performance
- Category
- Practical/ Demonstration
- Weight
- 20%
- Due date
14/04/2025 - 2/05/2025
Conducted in Allocated Prac
- Learning outcomes
- L04, L06, L07
Task description
Demonstration of the Cellular Machines lab in prac sessions. Simulating the Game of Life and other cellular machines.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
There are grade hurdles associated with this practical. See Course grading section.Submission guidelines
Lab sheet requirements are demonstrated to the teaching team during your allocated practical session.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Prac demos are completed as part of a scheduled prac class.
If there are exceptional circumstances, an exemption may be approved and may involve submitting/discussing your work as it stands. Exemptions must be requested as an extension with a note specifying exemption via my.UQ.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Computational Models
- Hurdle
- In-person
- Mode
- Activity/ Performance
- Category
- Practical/ Demonstration
- Weight
- 20%
- Due date
19/05/2025 - 30/05/2025
Conducted in Allocated Prac
- Learning outcomes
- L02, L03, L05, L08, L09
Task description
Demonstration of the Computational Models lab in prac sessions. Problems include solving the Deutsch problem using IBM's quantum computer - QisKit etc.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
There are grade hurdles associated with this practical. See Course grading section.Submission guidelines
Lab sheet requirements are demonstrated to the teaching team during your allocated practical session.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Prac demos are completed as part of a scheduled prac class.
If there are exceptional circumstances, an exemption may be approved and may involve submitting/discussing your work as it stands. Exemptions must be requested as an extension with a note specifying exemption via my.UQ.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Final Examination
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Learning outcomes
- L02, L03, L04, L05, L06, L08, L09
Task description
A 120-minute examination will be held during the examination period. Students will sit an on-campus invigilated exam.
The exam will cover content from the whole semester.
Hurdle requirements
There are grade hurdles associated with the final exam. See grades section.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed Book examination - no written materials permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: A Grade of 1 will be awarded for an overall mark below 20%. |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: A Grade of 2 will be awarded for an overall mark below 47% but greater than or equal to 20%. |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: A Grade of 3 will be awarded for an overall mark below 50% but greater than or equal to 47%, while also not meeting the requirements for higher grades. |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: A Grade of 4 will be awarded for an overall mark below 65% but greater than or equal to 50%, passed at least 2 out of a possible 3 main demonstration assessments and at least 40% on the final exam. |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: A Grade of 5 will be awarded for an overall mark below 75% but greater than or equal to 65%, completed and passed all 3 possible main demonstration assessments and passed the final exam. |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: A Grade of 6 will be awarded for an overall mark below 85% but greater than or equal to 75%, completed and passed all 3 possible main demonstration assessments and obtained greater than 75% onﾠthe final exam. |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: A Grade of 7 will be awarded for an overall mark of 85% or greater, completed and passed all 3 possible main demonstration assessments and obtained greater than 85% on theﾠ final exam |
Additional course grading information
Note that 'passing' assessments is defined as obtaining 50% or more on that assessment. Marks will be rounded for computing the grade hurdles and the final grade.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Having Troubles?
If you are having difficulties with any aspect of the course material, you should seek help and speak to the course teaching staff. If external circumstances are affecting your ability to work on the course, you should seek help as soon as possible. The University and UQ Union have organisations and staff who are able to help; for example, UQ Student Services are able to help with study and exam skills, tertiary learning skills, writing skills, financial assistance, personal issues, and disability services (among other things). Complaints and criticisms should be directed in the first instance to the course coordinator. If you are not satisfied with the outcome, you may bring the matter to the attention of the School of EECS Director of Teaching and Learning.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
Watch the ComputationﾠYouTubeﾠPlaylist of the covered topics created for this course.
Dr. Chandra will provide a draft of his book on the subject to be freely provided and used during the course.
Additional Reading:
Essential Turing : Classic Writings on Minds and Computers, edited by B. Jack. Copeland, Oxford University Press, 2004. ProQuest Ebook Central.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks |
Lecture |
Lecture Sessions Course topics delivered lecture and contact style. Learning outcomes: L01, L02, L03, L04, L05, L06, L08, L09 |
Not Timetabled |
Videos and Reading Videos (via a YouTube playlist) and reading materials will be provided for topics necessary and of interest to the course. It is expected that students spend a good amount of time studying these recommended materials. Learning outcomes: L08 |
|
Tutorial |
Contact Sessions Understanding the theoretical aspects of theories of computation. Learning outcomes: L01, L02, L03, L04, L05, L06, L08 |
|
Practical |
Laboratory Python lab sheets for building and understanding theories of computation. Learning outcomes: L03, L04, L06, L07, L08, L09 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: