Unit outline_

AMSI4001: AMSI Summer School

Intensive January, 2026 [Block mode] - Camperdown/Darlington, Sydney

The Australia-wide community in the Mathematical Sciences offers rich intellectual resources beyond what is available at the University of Sydney alone. This unit will enable you to access some of those resources by taking a course at the annual Australian Mathematical Sciences Institute (AMSI) Summer School, and in this way engage with staff and other students from all over the country. This annual residential summer school provides a range of courses taught by eminient researchers from across Australia for honours and postgraduate students. You will study an area of Mathematics of Statistics beyond what is typically available at the University of Sydney. You will also meet students from other universities, learn about Mathematical topics of general interest through public lectures and lectures especially designed for summer School participants, and take part in a career information event. By doing this unit, you will develop expertise in a specialist area of Mathematics and Statistics at an advanced level, broaden your horizons to develop a deeper understanding of the role of the Mathematical Sciences beyond the university sector, and begin to form a network of peers across Australia.

Unit details and rules

Academic unit Mathematics and Statistics Academic Operations
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Completion of a Bachelor's degree with a major in Mathematics, Statistics, Financial Mathematics and Statistics, Data Science, Discrete Mathematics and Algorithms, Mathematical Modelling and Computation, or equivalent.

Available to study abroad and exchange students

No

Teaching staff

Coordinator Laurentiu Paunescu, laurentiu.paunescu@sydney.edu.au
The census date for this unit availability is 23 January 2026
Type Description Weight Due Length Use of AI
Written exam Exam
Follow the assessment as prescribed for the course you have signed up.
100% Formal exam period 2 hours AI prohibited
Outcomes assessed: LO1 LO2 LO3 LO4

Assessment summary

As per the chosen course.

Assessment criteria

As per course information.

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:

As per the chosen course.

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.

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

WK Topic Learning activity Learning outcomes
Week 01 As per chosen subject Lecture (4 hr)  
As per chosen subject. Tutorial (3 hr)  
Week 02 As per chosen subject. Lecture (4 hr)  
As per chosen subject. Tutorial (3 hr)  
Week 03 As per chosen subject. Lecture (4 hr)  
As per chosen subject. Tutorial (3 hr)  
Week 04 As per chosen subject. Lecture (4 hr)  
As per chosen subject. Tutorial (3 hr)  

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 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. Develop advanced disciplinary expertise in a specialist ares of mathematics and statistics.
  • LO2. Develop advanced disciplinary expertise in a specialist ares of mathematics and statistics.
  • LO3. Develop and communicate an appreciation of one's own learning style, role within the discipline and potential career trajectories and professional networks.
  • LO4. ​Use advanced disciplinary knowledge to analyse and apply theory and to creatively synthesise material to perform calculations, generate proofs and solve problems.​

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.

Not applicable.

Disclaimer

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