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Unit outline_

MATH3976: Mathematical Computing (Advanced)

Semester 1, 2024 [Normal day] - Camperdown/Darlington, Sydney

This unit of study provides an introduction to programming and numerical methods. Topics covered include computer arithmetic and computational errors, systems of linear equations, interpolation and approximation, solution of nonlinear equations, quadrature, initial value problems for ordinary differential equations and boundary value problems, and optimisation.

Unit details and rules

Academic unit Mathematics and Statistics Academic Operations
Credit points 6
Prerequisites
? 
A mark of 65 or above in [(12cp of MATH2XXX) or (6cp of MATH2XXX and 6cp of STAT2XXX or DATA2X02)]
Corequisites
? 
None
Prohibitions
? 
MATH3076 or MATH4076
Assumed knowledge
? 

Strong skills in linear algebra and the theory and methods of ordinary and partial differential equations for example (MATH2961 and MATH2965) or (MATH2921 and MATH2922)

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Ayesha Sohail, ayesha.sohail@sydney.edu.au
The census date for this unit availability is 2 April 2024
Type Description Weight Due Length
Supervised exam
? 
Final Exam
See Canvas for more details
50% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Assignment Assignment 1
Assignment
10% Week 03
Due date: 06 Mar 2024 at 23:59
Standard assessment
Outcomes assessed: LO1 LO2 LO4 LO5
Assignment Assignment 2
Assignment
15% Week 08
Due date: 17 Apr 2024 at 23:59
Standard assessment
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Online task Online quiz
Quiz
10% Week 09
Due date: 26 Apr 2024 at 13:00

Closing date: 27 Apr 2024
1 hour
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Assignment Project
Written report on modelling project
15% Week 13
Due date: 22 May 2024 at 23:59
Standard assessment
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6

Assessment summary

Detailed information for each assessment can be found on Canvas.

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.

Result name

Mark range

Description

High distinction

85 - 100

Representing complete or close to complete mastery of the material.

Distinction

75 - 84

Representing excellence, but substantially less than complete mastery.

Credit

65 - 74

Representing a creditable performance that goes beyond routine knowledge and understanding, but less than excellence.

Pass

50 - 64

Representing at least routine knowledge and understanding over a spectrum of topics and important ideas and concepts in the course.

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

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.

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
Week 01 Matlab basics, fundamentals of computational algorithms, and root finding methods (hint: Chapters 5 and 6 from Steven C Chapra). Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5
Week 02 Matrices (Iterative and non-iterative methods). it will help you to revise and learn basics of numerical Linear Algebra. (chapters 9, 10, 11, 12). Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5
Week 03 Worked examples and applications of topics learnt during weeks 1 and 2 practically. Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5
Week 04 Numerical integration. Chapters 21 and 22 Lecture and tutorial (4 hr) LO1 LO2 LO3 LO5
Week 05 Numerical differentiation. Chapters 23 and 24. Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5
Week 06 Interpolation and Fourier transforms. Chapters 18 and 19. Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5
Week 07 Review of what we learnt so far. Challenge questions. Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5
Week 08 Differential equations and their numerical solution. Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5
Week 09 Unconstrained optimization. Chapter 13. Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5 LO6
Week 10 Constrained optimization. Chapters 15 and 16. Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 11 Some further understanding of optimization. Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5 LO6
Week 12 Machine learning. What we know. Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 13 Mathematical computing and machine learning. Lecture and tutorial (4 hr) LO1 LO2 LO4 LO5 LO6

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. apply the basic ingredients of any programming language including syntax, definition of variables, control structures and memory management
  • LO2. investigate and resolve sources of error in numerical computation
  • LO3. explain how binary and floating-point decimal numbers are represented on a computer
  • LO4. leverage and compute linear operations on data
  • LO5. create numerical routines using fundamental numerical methods to solve computational problems in science, engineering and mathematics
  • LO6. create reports, that combine a description of a practical problem, its numerical framing and the results of computation to solve this problem.

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.

No changes have been made since this unit was last offered.

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

General Laboratory Safety Rules

  • No eating or drinking is allowed in any laboratory under any circumstances
  • A laboratory coat and closed-toe shoes are mandatory
  • Follow safety instructions in your manual and posted in laboratories
  • In case of fire, follow instructions posted outside the laboratory door
  • First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory
  • As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

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.