Note: This unit version is currently being edited and is subject to change!
ENGG1810: Introduction to Engineering Computing (2021 - Semester 2)
| Unit: | ENGG1810: Introduction to Engineering Computing (6 CP) |
| Mode: | Normal-Day |
| On Offer: | Yes |
| Level: | Junior |
| Faculty/School: | School of Computer Science |
| Unit Coordinator/s: |
Dr Takatsuka, Masahiro
|
| Session options: | Semester 1, Semester 2 |
| Versions for this Unit: |
| Campus: | Camperdown/Darlington |
| Pre-Requisites: | None. |
| Prohibitions: | ENGG1801 OR INFO1110 OR INFO1910 OR INFO1103 OR INFO1903 OR INFO1105 OR INFO1905 OR COSC1003. |
| Brief Handbook Description: | This unit is an essential starting point for engineers to learn the knowledge and skills of computer programming, using a procedural language. Crucial concepts include defining data types, control flow, iteration, and functions. Students will learn to translate a general engineering problem into a computer program. This unit trains students in the software development process, which includes programming, testing and debugging. |
| Assumed Knowledge: | None. |
| Tutor/s: | TBC | ||||||||||||||||||||
| Timetable: | ENGG1810 Timetable | ||||||||||||||||||||
| Time Commitment: |
|
||||||||||||||||||||
| T&L Activities: | Tutorial: Computer Laboratory. |
Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.
(6) Communication and Inquiry/ Research (Level 1)| Assessment Methods: |
|
||||||||||||||||||||||||||||||
| Assessment Description: |
Assessment breakdown: 20% Tutorial quizzes - 2x paper written quizzes, lasts length of tute 20% Lab exercises - Weekly online programming task (after having practised at home) 10% Lab exam - 2x lockdown tests in computer lab 50% Final exam - Written paper exam |
| Prescribed Text/s: |
Note: Students are expected to have a personal copy of all books listed.
|
| Recommended Reference/s: |
Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.
|
Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp
| Week | Description |
| Week 1 | Lecture/Tutorial: Introduction to Python |
| Week 2 | Lecture/Tutorial: Variables and data types, operators, expressions, logical |
| Week 3 | Lecture/Tutorial: Control flow, conditionals |
| Week 4 | Lecture/Tutorial: Loops |
| Week 5 | Lecture/Tutorial: Functions |
| Week 6 | Lecture/Tutorial: Collections (arrays, lists, dictionaries) |
| Week 7 | Lecture/Tutorial: Classes |
| Week 8 | Lecture/Tutorial: File input/output, exceptions |
| Week 9 | Lecture/Tutorial: Testing methods and debugging |
| Week 10 | Lecture/Tutorial: Introduction to numpy, numerical integration |
| Week 11 | Lecture/Tutorial: Statistics, curve fitting and regression |
| Week 12 | Lecture/Tutorial: Basic optimisation (Newton’s method) |
| Week 13 |
Lecture/Tutorial: 2D/3D data visualisation. Course review. Final examination overview. |
| Exam Period | Assessment Due: Final graded exam (paper written exam) |
Course Relations
The following is a list of courses which have added this Unit to their structure.
Course Goals
This unit contributes to the achievement of the following course goals:
These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.
