• Class Number 3567
  • Term Code 3030
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Dr Kenneth Duru
  • LECTURER
    • Dr Kenneth Duru
  • Class Dates
  • Class Start Date 24/02/2020
  • Class End Date 05/06/2020
  • Census Date 08/05/2020
  • Last Date to Enrol 02/03/2020
SELT Survey Results

This course presents the basic elements of scientific computing, in particular the methods for solving or approximating the solution of calculus and linear algebra problems associated with real world problems. Using a non-trivial model problem such as the heat equation, and sophisticated scientific computing and visualisation environments, students are introduced to the basic computational concepts of stability, accuracy and efficiency, as new numerical methods and techniques are introduced to solve progressively more challenging problems.

Honours Pathway Option (HPO):

To do this option, students must have completed MATH2405 or STAT2001 or a mark of 60% or more in MATH2305 or MATH1116. The HPO expands on the theoretical aspects of the underlying algorithms, and uses alternative assessment to assess these theoretical aspects.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

On satisfying the requirements of this course, students will have the knowledge and skills to:

1. Use high-level programming language such as Python with proficiency and confidence
2. Use appropriate tools to verify the output and reliability of code/data
3. Use computing and visualisation software appropriately in scientific or engineering problems

Examination Material or equipment

  • Course/lecture notes are allowed.
  • Any number of copied or hand written pages.
  • Any unmarked Calculus textbook.
  • Unmarked English-to-foreign-language dictionary (no approval from MSI required).
  • Any hand calculator.
  • No electronic aids with internet access are permitted e.g. laptops, phones, ipad.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Class Schedule

Week/Session Summary of Activities Assessment
1 Course overview. Introduction to Python. Numbers and their representation. Lectures 1-3 Lab 0: Introduction to programming in Python and Jupyter Notebooks. This Lab is a hurdle but it carries a zero weight. Due: March 11.
2 Floating point numbers. Rounding errors. Conditioning and stability. Lectures 4-6 Assignment 1: Will assess floating point numbers, rounding errors, conditioning and stability. Due: March 16
3 Norms. Direct solvers. Pivoting. Lectures 7-8 Lab 1: Synthesis of rounding errors. Due: March 23
4 Iterative methods. Gradient based methods. Bisection methods for nonlinear problems. Lectures 9-11 Assignment 2: Direct and iterative methods. methods for nonlinear problems. Due: March 30
5 Fixed point theorem. High order methods (Newton, Secant, Regula falsi methods) Lectures 12-14 Lab 2: Implement direct and iterative solver for linear equations. Newton/Secant method for nonlinear equations Due: April 5
6 Advanced iterative methods: SOR and Iterative refinement. Lectures 15-17 Assignment 3: polynomial interpolation Due: April 24
7 Polynomial interpolation. Interpolation errors. Chebyshev interpolation. Lectures 18-20 Lab 3: Implementation of polynomial interpolation. Investigate accuracy and efficiency Due: April 30
8 Splines. Numerical differentiation: finite difference. method of undetermined coefficients. Richardson's extrapolation Lectures 21-23 Assignment 4: Numerical differentiation and integration Due: May 08
9 Numerical quadrature: Base rules. Newton-Cotes. Gauss quadrature. Lectures 24-26 Lab 4: Quadrature and numerical differentiation Due: May 14
10 Numerical methods for ODEs. Ones-step methods. Stability. Consistency. Lectures 27-29 Assignment 5: Analysis of numerical methods for ODEs Due: May 22
11 Runge-Kutta Methods. Multi-step methods. Lectures 30-32 Lab 5: Implementation of ODE solvers in Python. Synthesis of of numerical errors. Stability. Convergence. Due: May 28
12 BDF Methods. Revision Lectures 31-33

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Lab activities 30 % * * 1,2,3,
Written assignments 30 % * * 1,2,3,
End of semester exam 40 % 04/06/2020 02/07/2020 1,2,3,

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Examination(s)

The date range in the Assessment Summary indicates the start of the end of semester exam period and the date official end of semester results are released on ISIS. Please check the ANU final Examination Timetable http://www.anu.edu.au/students/program-administration/assessments-exams/examination-timetable to confirm the date, time and location exam.

Assessment Task 1

Value: 30 %
Learning Outcomes: 1,2,3,

Lab activities

Tutorial lab books evaluate the skills in implementation and practical applications of the methods using the Python programming language.

There are 6 lab books to be submitted fortnightly.

Lab-book 0 is hurdle but has a 0 weight.

Lab books 1 to 5 are assessed and weigh 30% of the overall grade.

Students are encouraged to work in groups, but each student must turn in her/his own Lab book.

Submitted Lab books will be corrected and returned to students seven days after the deadline


Further details can be found on the Course Wattle site.

Assessment Task 2

Value: 30 %
Learning Outcomes: 1,2,3,

Written assignments

Assignments provide feedback on the current level of understanding of the fundamental concepts and algorithms covered in the course so far.

There are 5 written assignment to be submitted fortnightly.

Assignments 1 to 5 are assessed and weigh 30% of the overall grade.

Students are encouraged to work in groups, but each student must turn in her/his own written assignment.

Submitted assignments will be corrected and returned to students seven days after the deadline


Further details can be found on the Course Wattle site.


Assessment Task 3

Value: 40 %
Due Date: 04/06/2020
Return of Assessment: 02/07/2020
Learning Outcomes: 1,2,3,

End of semester exam

The date range in the Assessment Summary indicates the start of the end of semester exam period and the date official end of semester results are released on ISIS. Please check the ANU final Examination Timetable http://www.anu.edu.au/students/program-administration/assessments-exams/examination-timetable to confirm the date, time and location exam.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.


The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.


The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission


  • Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

Assignments and Lab books will be returned via Wattle

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Depending on the circumstances of the student resubmission can be permitted.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Kenneth Duru
Kenneth.Duru@anu.edu.au

Research Interests


Numerical analysis

High order accurate and time-stable methods: finite difference methods, discontinuous Galerkin methods, spectral element methods

Provably accurate software for computational mechanics.

High performance computing

Partial differential equations.

Computational geophysics

Dr Kenneth Duru

Wednesday 10:00 12:00
Dr Kenneth Duru
61252908
Kenneth.Duru@anu.edu.au

Research Interests


Dr Kenneth Duru

Wednesday 10:00 12:00

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions