General information#
- A/Prof. Dan Andrews is your lecturer in the 1st half of the semester.
- Dr. Brian Parker is your lecturer in the 2nd half of the semester.
- Lectures twice a week: Monday, 10-11AM & Tuesday, 4-5PM.
- All lectures take place in the Llewelyn Hall, School of Music, Bldg 100.
- Livestream lectures and recordings available on echo360, see the link on Course Wattle page.
- Lecture slides and other materials will be available from [Course Wattle page] (https://wattlecourses.anu.edu.au/course/view.php?id=45343) and Ed Lessons (coming soon).
Schedule#
Links to slides and code will be available on the lecturing dates.
| Week | Date/Time | Lecture | Topic and Slides | ||
|---|---|---|---|---|---|
| 1 | 17/02/25 | 1 | Intro to programming (and COMP1730/6730) | ||
| 18/02/25 | 2 | Variable types and operators | |||
| 2 | 24/02/25 | 3 | Functions | ||
| 25/02/25 | 4 | Functional abstraction | |||
| 3 | 03/03/25 | 5 | Branching | ||
| 04/03/25 | 6 | Iteration | |||
| 4 | 10/03/25 | - | No Lecture: Canberra Day holiday | ||
| 11/03/25 | 7 | Coding Best Practices & Sequences:Strings | |||
| 5 | 17/03/25 | 8 | Sequences: Strings | ||
| 18/03/25 | 9 | Sequences: Lists | |||
| 6 | 24/03/25 | 10 | Files and IO | ||
| 25/03/25 | 11 | Modules and classes | |||
| Teaching break | |||||
| 7 | 14/04/25 | 12 | Introduction to scientific libraries with Numpy | ||
| 15/04/25 | 13 | Data analysis with Pandas and visualisation | |||
| 8 | 21/04/25 | 14 | Debugging and testing | ||
| 22/04/25 | 15 | Dictionaries and sets | |||
| 9 | 28/04/25 | 16 | Previous lectures continued. | ||
| 29/04/25 | 17 | Errors and exceptions | |||
| 10 | 06/05/25 | 18 | Computational Complexity | ||
| 07/05/25 | 19 | Algorithm design paradigms: Dynamic programming | |||
| 11 | 12/05/25 | 20 | Computational methods in science and engineering:scikit-learn | ||
| 13/05/25 | 21 | Computational methods in science and engineering:scikit-learn2 | |||
| 12 | 19/05/25 | 22 | Design and review | ||
| 20/05/25 | 23 | Design and review2 | |||
Recommended reading#
Find below some recommended reading if you want to come better prepared to the lectures and/or reinforce your understanding afterwards.
| Week | Recommended readings |
|---|---|
| 1 | Downey, chapters 1-2. Sundnes, Sects. 2.1-2.2 and 4.1-4.3, 4.5-4.7 |
| 2 | Downey, chapters 3, 4 and 6. Sundnes, chapter 4. docs.python.org Sections 4.7 & 4.8 |
| 3 | Downey, chapters 5 and 7. Sundnes, Sects. 3.1, 3.2, 3.4, 4.4. docs.python.org, 4.1 to 4.5 |
| 4 | Downey, chapter 8. |
| 5 | Downey, chapter 8, 10, 11 and 12. Sundnes, Section 3.3, 3.6, 7.1 and 7.4. docs.python.org, 3.1, 5.1.0, 5.1.1, 5.1.2, 5.3 and 5.5 |
| 6 | Downey, chapter 14. docs.python.org, 6.0, 6.1, 7.2, 9.3 |
| 7 | Sundnes, chapter 6. (excluding section 6.4) |
| 8 | Downey, chapter 7 and parts of 13. Sundnes, Section 4.7 (test functions) 7.1, 7.2, 7.3. docs.python.org, 5.4 and 5.5 |
| 9 | Downey, chapter 20 (called “Appendix A” in the on-line edition), chapter 14 section “Catching Exceptions”. Sundnes, Section 5.5 |
| 10 | Downey, chapter 21 (“Analysis of Algorithms”, called Appendix B in the on-line edition) introduces complexity analysis of algorithms. |
| 11 | Downey, 18.7 covers class inheritance. Sundnes, Section 9.1 covers class inheritance |
| 12 | Downey, 3.10 briefly covers pure functions (strangely referred to using the non-standard name “fruitful” functions). |