• Offered by School of Computing
  • ANU College ANU College of Engineering Computing & Cybernetics
  • Course subject Computer Science
  • Areas of interest Medical Science, Psychology, Statistics, Bioinformatics, Materials Science More...
  • Academic career UGRD
  • Course convener
    • Dr Brian Parker
    • Dr Dan Andrews
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in First Semester 2024
    Second Semester 2024
    See Future Offerings
  • STEM Course

This course teaches introductory programming, fundamental programming language and computer science concepts, and computational problem solving illustrated with applications common in science and engineering, such as simulation and data analysis and visualisation. The course does not require any prior knowledge of programming, computer science or IT. There is an emphasis on designing and writing correct programs: testing and debugging are seen as integral to the programming enterprise.

Learning Outcomes

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

  1. Design and write programming code to solve practical problems of a scientific or engineering nature.
  2. Ability to read, test and debug small computer programs.
  3. Ability to use key python libraries for data processing and visualisation.
  4. Understanding of widely-used algorithms and data structures, and their computational complexity.
  5. Apply design approaches used in scientific pipelines, including data abstraction and array-based and object-oriented programming.
  6. Understand and apply principles of high code quality.
  7. Communicate effectively to both specialist and non-specialist audiences about data processing problems in writing and verbally.

Other Information

Course Webpage

Indicative Assessment

  1. Practical programming assessments (15) [LO 1,2,3,4]
  2. Project Assignment (35) [LO 1,2,3,4,5,6,7]
  3. Exam (50) [LO 1,2,3,4,5,6]

The ANU uses 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. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

4 hours scheduled time each week (2 lectures and one 2-hour lab).

Students are expected to spend an average of 5-6 hours per week practicing programming (including work on assignments) outside of scheduled labs.

Inherent Requirements

None.

Requisite and Incompatibility

You are not able to enrol in this course if you have successfully completed COMP6730

Prescribed Texts

There are no prescribed texts.


Preliminary Reading

We recommend:

"Think Python: How to think like a computer scientist" (2nd Edition) by Allan Downey. Available from http://greenteapress.com/wp/think-python-2e/, or in paperback (O'Reilly, 2015; ISBN-13: 978-1491939369; ISBN-10: 1491939362).

Introduction to Scientific Programming with Python, by Joakim Sundnes (published by Springer, 2020).

Assumed Knowledge

Students are assumed to have achieved a level of knowledge of mathematics comparable to at least ACT Mathematics Methods or NSW Mathematics or equivalent.

No programming, Computer Science or IT experience or skills are required

Areas of Interest

  • Medical Science
  • Psychology
  • Statistics
  • Bioinformatics
  • Materials Science
  • Photonics
  • Physics
  • Science
  • Engineering
  • Genetics
  • Mechatronics
  • Electronics
  • Communications
  • Biotechnology
  • Biomedical Science

Fees

Tuition fees are for the academic year indicated at the top of the page.  

Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees

Student Contribution Band:
2
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2024 $4980
International fee paying students
Year Fee
2024 $6360
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
4173 19 Feb 2024 26 Feb 2024 05 Apr 2024 24 May 2024 In Person View

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
9175 22 Jul 2024 29 Jul 2024 31 Aug 2024 25 Oct 2024 In Person N/A

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