Outline

Overview

This unit is an essential starting point for software developers, IT consultants, and computer scientists to build their understanding of principle computer operation. Students will obtain knowledge and skills with procedural programming. Crucial concepts include defining data types, control flow, iteration, functions, recursion, the model of addressable memory. Students will be able to reinterpret a general problem into a computer problem, and use their understanding of the computer model to develop source code. This unit trains students with software development process, including skills of testing and debugging. It is a prerequisite for more advanced programming languages, systems programming, computer security and high performance computing.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	INFO1910 or INFO1103 or INFO1903 or INFO1105 or INFO1905 or ENGG1810
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	David Lowe, david.lowe@sydney.edu.au
Lecturer(s)	David Lowe, david.lowe@sydney.edu.au
	Julian Mestre, julian.mestre@sydney.edu.au
	Elliot Varoy, elliot.varoy@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 exam ?	Final Examination Final exam: Contains both foundation and advanced components.	0%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Practical skill	Assignment slot 2 Computer programming problems (Submission 1) : Foundation assignment (for marking) + (optional) Advanced assignment (for feedback)	0%	Mid-semester break Due date: 04 Oct 2025 at 23:59 Closing date: 09 Oct 2025	-	AI allowed
Outcomes assessed:
In-class quiz	Foundation Quiz In-class invigilated quiz in weeks 8,10, & 12.	0%	Multiple weeks	-	AI allowed
Outcomes assessed:
Q&A following presentation, submission or placement	Code Review 4 Oral code review for Foundation Assignment OR Advanced Assignment	0%	STUVAC Due date: 10 Nov 2025 at 08:00	-	AI prohibited
Outcomes assessed:
Out-of-class quiz	Early Feedback Task #earlyfeedbacktask Completion of online quiz to assess module progress	0%	Week 03 Due date: 24 Aug 2025 at 23:59 Closing date: 24 Aug 2025	-	AI allowed
Outcomes assessed:
Practical skill	Assignment slot 1 Computer programming problems (Submission 1) : Foundation assignment (for marking) + (optional) Advanced assignment (for feedback)	0%	Week 06 Due date: 13 Sep 2025 at 23:59	-	AI allowed
Outcomes assessed:
Q&A following presentation, submission or placement	Code Review 1 Oral code review for Foundation Assignment	0%	Week 08 Due date: 22 Sep 2025 at 08:00	-	AI prohibited
Outcomes assessed:
Q&A following presentation, submission or placement	Code Review 2 Oral code review for Foundation Assignment	0%	Week 10 Due date: 13 Oct 2025 at 08:00	-	AI prohibited
Outcomes assessed:
Practical skill	Assignment slot 3 Computer programming problems (Submission 1) : Foundation assignment (for marking) + (optional) Advanced assignment (for marking)	0%	Week 11 Due date: 25 Oct 2025 at 23:59 Closing date: 30 Oct 2025	-	AI allowed
Outcomes assessed:
Q&A following presentation, submission or placement	Code Review 3 Oral code review for Foundation Assignment OR Advanced Assignment	0%	Week 13 Due date: 03 Nov 2025 at 08:00	-	AI prohibited
Outcomes assessed:
= hurdle task ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

The assessment in this unit is structured in an unusual way. There are 2 different assessment types – assignments and tests (as well as an early feedback task that does not affect your grade), and these are split into Foundation tasks and Advanced tasks.

	Foundation	Advanced
Test	Foundation Tests: 4 attempts (in weeks 8, 10, 12 and final exam) pass/fail only	Advanced Test: 1 attempt (in final exam) 30 marks
Assignment	Foundation Assignment: 3 attempts (in weeks 6, mid-sem, and 11, with oral reviews in weeks 8, 10, 13 and stuvac) pass/fail only	Advanced Assignment: 2 submissions for feedback (weeks 6, mid-sem) and 1 submission for marking (week 11) with oral code review in weeks 13 or stuvac. 20 marks
General notes	These tasks are only pass/fail and are hurdle tasks. Both must be passed to achieve a 50P result.	These tasks are both optional. They are marked, with the marks being added once a 50P has been achieved in the Foundation tasks.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

For more information see sydney.edu.au/students/guide-to-grades.

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:

The usual University policy is that you are penalized 5% per day for late submissions (up to a maximum of 10 days). Since the Foundation tasks in this unit don't have marks awarded (being purely pass/fail) applying a percentage penalty doesn't make sense. Instead, you are penalised 0.5 marks per day for late submissions.

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
Week 01	What is a computer program?	Workshop (2 hr)
Week 02	Variables and data types, operators and expressions, comments, input() function, files and folders.	Workshop (2 hr)
Week 03	The if statement, indented blocks, testing and debugging	Workshop (2 hr)
Week 04	Python Containers (list, tuples, dictionaries), testing and debugging	Workshop (2 hr)
Week 05	For loops	Workshop (2 hr)
Week 06	While loops, handling errors	Workshop (2 hr)
Week 07	Python functions and scope	Workshop (2 hr)
Week 08	Input and output	Workshop (2 hr)
Week 09	Classes	Workshop (2 hr)
Week 10	Characters and list comprehensions	Workshop (2 hr)
Week 11	Function parameters, Sets	Workshop (2 hr)
Week 12	Recursive functions	Workshop (2 hr)
Week 13	Numerical python	Workshop (2 hr)
Weekly	A series of Ed Lessons involving recorded videos and exercises are released for students to work through independently. Different schedule recommendations are customised for each student to help them achieve the learning outcomes they want to target.	Independent study (3 hr)
	Weekly reviews of the unit content catered to student feedback from the Ed Lessons. Two different options weekly, targeted at students’ differing progress.	Seminar (2 hr)
	Each workshop will feature group and independent exercises to reinforce the Ed Lesson content. There will be four different zones available, each catered to different progression through the unit content.	Workshop (2 hr)

Attendance and class requirements

Workshop classes are designed to assist students with progressing through the unit and demonstrating competence in this unit.

Participation in all workshops is mandatory, and attendance will be checked. Any student who attends less then 10 workshops will be automatically awarded an AF (Absent Fail) result for the unit.

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.

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.

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

LO1. employ programming style conventions for writing consistently readable code
LO2. design and construct new functionality to existing procedural program or function
LO3. compose a structured algorithmic design to solve the descriptive problem specification
LO4. compose an entire procedural program from descriptive problem specification
LO5. demonstrate an understanding of programming principles, data types, variables and operators, control-flow: simple statement, sequence, if-then-else, while, functions: stack, input/output, reference memory model
LO6. compose, analyse and trace procedural code, scoping/variable lifetime, memory of the stack, references and globals, data types, operations on data types
LO7. construct code cliches for input and manipulating arrays, including maximum, minimum, search or traverse, with actions on each element for counting or summation
LO8. construct and assess code for recursively-defined numerical functions, and for recursively described array manipulations
LO9. apply testing methods and assess programs through debugging with the ability to write a set of tests for a small program or function
LO10. explain compilation process and debugging mechanism
LO11. use standard library functions

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

Alignment with Competency standards

Outcomes	Competency standards
	Engineers Australia Curriculum Performance Indicators - 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
	Engineers Australia Curriculum Performance Indicators - 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.3. Creativity and innovation.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity. 3.3. Creativity and innovation. 4.1. Advanced level skills in the structured solution of complex and often ill defined problems.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.1. An ability to communicate with the engineering team and the community at large.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.3. Creativity and innovation.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.1. An ability to communicate with the engineering team and the community at large. 3.2. Information literacy and the ability to manage information and documentation. 5.4. Skills in the selection and application of appropriate engineering resources tools and techniques, appreciation of accuracy and limitations;. 5.7. Proficiency in appropriate laboratory procedures; the use of test rigs, instrumentation and test equipment. 5.8. Skills in recognising unsuccessful outcomes, sources of error, diagnosis, fault-finding and re-engineering.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 3.1. An ability to communicate with the engineering team and the community at large.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.1. An ability to communicate with the engineering team and the community at large.

Responding to student feedback

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

A radically different model for teaching the unit was trialled in Semester 2, 2024, based around adapting to the learning needs of different students. This was successful and so was refined in semester 1, 2025. Based on tutor, USS and coordinator feedback, further refinements are being made. Workshop zones will be more refined to improve engagement with tutors. Advanced tasks are being managed differently to provide more opportunity for students to engage with the advanced content, even late into the semester.

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

INFO1110: Introduction to Programming

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

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links