This website is for the Semester 1, 2023 version of COMP1730/6730.

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Practical information

Note: This applies to both COMP1730 and COMP6730.

Please check important start of semester TODOs here. !!!

Remote participation

It will be possible to participate in the course on-line. Both on-line and on-campus lab options are offered. Please check the timetable for lab times and venues.

The majority of lab places this semester are on-campus. They are however unfortunately concentrated on Mondays, mornings and evenings.

Students in Canberra are strongly encouraged to attend on-campus if able to. On-line labs are however available to everyone and are not restricted to students outside of Canberra. Students who are on campus should be able to use InfoCommons and CS lab computers to participate in on-line labs from on-campus if needed.

To study remotely, you must have:

More information about the software requirements and how to setup and use the VDI is available on the labs page.

Course material and where to find it

All course material will available through this web site and the course wattle page. The wattle page will be used for interactive functions and non-public information, such as forums, teams codes, quizzes, and assignment submissions, while course material such as lecture slides, lab pages and assignment specifications will be found here (see the lectures, labs and assessments tabs at the top of the page).

Lectures are every Monday and Tuesday, 10am-11am and 2pm-3pm respectively, both at Copland T (note: not Coombs T, don’t mix them up they’re pretty far apart!). Lectures will also be available online. Note that there may not be a lecture on some days. Please check the content and schedule page.

We will be using teams for you to interact with tutors during labs (if you are attending labs online). You should be able to log into teams using your ANU id (uNNNNNNN). There will be separate teams for lectures and for each of the lab groups: to join a team you will need an access code, which will be posted on the course wattle page.

Live lectures will be recorded so that you can watch them later if you cannot attend. The details will be posted on the content and schedule page and the course Wattle page.

Teachers

The course convenors and lecturers in Semester 1 are Brian Parker and Dan Andrews.

Tutor info will be listed on the course Wattle page before the first lab here.

Contact information

  • Any questions about course content — in other words, questions about programming, about what will be assessed, about when the next lecture is - should be posted to the discussion forum on wattle. When using the forum, consider this:

    1. Before you post a question, read the answers to the relevant questions that have already been asked. Do not repeat the same question. If you do not understand the previous answer, repeating the same question is not going to give you a different answer. Try to explain what it is that you’re missing in the previous answer.
    2. When you start a new thread, give it a descriptive topic. This will help others find your question (and the answer to it) and therefore make it easier for them to follow advice #1.
    3. Do not post solutions, or parts of solutions, to assignment problems. Not even after the deadline (we will post solutions if and when it is the right time to do so). Not even if they don’t work.

    We aim to reply to any questions posted to the forum within one working day. We will not always achieve this aim. (Also, “reply” does not always mean “answer”. Sometimes the best answer to a question is a counter-question, a pointer in a different direction, or something else other than a direct answer.)

  • Any questions for the teachers that you don’t want to discuss in public - for example, the reasons why you are unable to explain the content of your assignment submission, etc - email to comp1730@anu.edu.au. This email will be read by the teachers (both lecturers, and possibly some of the tutors). Emails will never be answered faster than questions posted to the wattle forum.

  • For any administrative questions (how to enroll, unenroll, rules relating to your degree, exams, etc), you should contact student services. They can also reached via email (studentadmin.cecs@anu.edu.au).

  • If you have any feedback (good or bad) about the course and you do not want to talk to the lecturer directly, your first point of contact is the student course representatives. Course reps will be chosen at the start of the semester - if you would like to volunteer, let us know by emailing comp1730@anu.edu.au.

Course outline

See the course page on ANU Programs & Courses for more information.

Description

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, visualisation and machine learning models. 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

Students who succeed in all aspects of COMP1730 will have the knowledge and skills to:

  • Design, write and debug programs in the python language to solve practical problems of a scientific or engineering nature.
  • Use key modules/libraries for computational analysis and visualisation of scientific and engineering data.
  • Have an awareness of good program organisation especially for scientific pipelines.
  • Have an understanding of widely-used algorithms and data structures, and their computational complexity.

In addition to the above, on successful completion COMP6730 students will have the knowledge and skills to:

  • Have an understanding of more advanced algorithm design paradigms such as dynamic programming with scientific applications.
  • Have an advanced understanding of data types and libraries used for data analysis and machine learning in python, including array-based programming.

Assumed knowledge

No programming, computer science or IT experience or skills are required. Students are assumed to have a level of knowledge of mathematics comparable to at least ACT Mathematics Methods, NSW Mathematics or equivalent.

Text books and other resources

We do not prescribe any specific text book, but strongly recommend that your acquire at least one. The following is recommended:

  • Think Python: How to think like a computer scientist, 2nd Edition, by Allan Downey.

    This book can be be found on-line, in PDF format or as set of web pages. For convenience, a copy of the PDF version is available here. The book is also available in paperback (published by O’Reilly, 2015; ISBN-13: 978-1491939369; ISBN-10: 1491939362).

    If you get this book, it is important that you get the 2nd edition, which is written for python 3.x.

This text book does not follow the structure of the course schedule exactly. We will provide reading guidance with the schedule.

There are many resources to help you learn programming on the web. We will post links to the best ones as we find them, and we invite you to do the same.

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