ENGG1801: Engineering Computing (2013 - Semester 1)
| Unit: | ENGG1801: Engineering Computing (6 CP) |
| Mode: | Normal-Day |
| On Offer: | Yes |
| Level: | Junior |
| Faculty/School: | School of Information Technologies |
| Unit Coordinator/s: |
Dr Chan, Jason
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| Session options: | Semester 1 |
| Versions for this Unit: | |
| Site(s) for this Unit: |
| Campus: | Camperdown/Darlington |
| Pre-Requisites: | None. |
| Brief Handbook Description: | The unit will introduce students to fundamental principles of programming. The language used will be Matlab but the principles taught are readily portable to other languages like C and Java. The unit material will be presented in a manner which will help students to draw a connection between programming constructs and real engineering applications. The unit will use engineering inspired case-studies : especially from Civil, Chemical, Aerospace and Mechanical streams, to motivate new material. There will be a major project which uses programming to solve a real world engineering problem. The extensive Matlab library for visualization will also be introduced. Matlab will cover two-thirds of the unit. The remaining one-third will be devoted to the use of Excel in engineering scenarios. Furthermore, cross integration between Matlab and Excel will also be highlighted. |
| Assumed Knowledge: | None. |
| Lecturer/s: |
Dr Chan, Jason
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| Tutor/s: |
Jason Chan Hao Chen Jen Jen Chung Manaal Fatima Jiro Funamoto Ken Ho Kelvin Hsu Angela Lui Ling Luo Mohsen Masoudian Ingrid McCarroll Shabnam Shayan |
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| Timetable: | ENGG1801 Timetable | ||||||||||||||||||||
| Time Commitment: |
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| T&L Activities: | Tutorial: computer laboratory |
Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.
| Attribute Development Method | Attribute Developed |
| The ability to comprehend a problem and translate it, using modelling skills into a set of logical program steps. | Design (Level 1) |
| Examples from Science and Engineering disciplines will be used. Methods of analysing specific problems in Civil, Aeronautical, Mechanical,Chemical and Biomedical Engineering will be studied. Basic programmings skills will be developed using MATLAB and EXCEL. Students will learn the fundamental pronciples of computer programming, syntax, logic statements, data storage, function usage, input and output. | Maths/Science Methods and Tools (Level 1) |
| Ability to use different systems for information retrieval, particularly in regard to ICT skills. | Information Seeking (Level 1) |
| The ability to interpret results and present solutions for problems in an acceptable report format. | Communication (Level 1) |
| Ability to apply self management skills to complete a programming project. Understanding the rules of copyright and appropriate usage of code. Understanding the role of computer programming in the management of projects. Students may chose to work in pairs in the project assignment. |
Professional Conduct (Level 1) |
For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table.
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.
Design (Level 1)
1. Understand basic concepts of computing such as abstraction, describing a solution of a problem as an algorithm and running Matlab programs. Ability to use MATLAB and EXCEL to model Engineering problems.
Maths/Science Methods and Tools (Level 1)
2. Understand fundamental programming concepts such as flow of control, loops, functions and parameters passing. Able to use basic data structures such as arrays and structures of heterogeneous objects.
3. Able to read and write data in Matlab from and in different formats and to interpret and process the data to obtain meaningful results. Able to plot data in 2 dimensions and use Matlab’s advanced 3-dimensional surface plots.
4. Able to carry out simple matrix computations including matrix sum, product, dot product, calculating the determinant and elementary functions on matrix.
5. Understand how digital images can be represented as matrices and operations on images can be abstracted as operations on matrices. Be aware of how imaging software products are based on matrix operations.Be able to identify the appropriate product for the particular class of engineering.
Communication (Level 1)
6. Ability to construct a mini project report using ICT tools.
Professional Conduct (Level 1)
7. Be aware of good practice in developing MATLAB and EXCEL applications. Be aware of requirements for software benchmarking and validation.
| Assessment Methods: |
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| Assessment Description: |
Lab Exercises: Programming tasks done in weekly labs Lab Exam: Practical programing test Major Project: Programming assignment Final Exam: Exam |
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| Grading: |
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| Faculty Policies & Procedures: | Academic Honesty in Coursework. All students must submit a cover sheet for all assessment work that declares that the work is original and not plagiarised from the work of others. Coursework assessment and examination policy. The faculty policy is to use standards based assessment for units where grades are returned and criteria based assessment for Pass/Fail only units. Norm referenced assessment will only be used in exceptional circumstances and its use will need to be justified to the Undergraduate Studies Committee. Special consideration for illness or misadventure may be considered when an assessment component is severely affected. This policy gives the details of the information that is required to be submitted along with the appropriate procedures and forms. Special Arrangements for Examination and Assessment. In exceptional circumstances alternate arrangements for exams or assessment can be made. However concessions for outside work arrangements, holidays and travel, sporting and entertainment events will not normally be given. Student Appeals against Academic Decisions. Students have the right to appeal any academic decision made by a school or the faculty. The appeal must follow the appropriate procedure so that a fair hearing is obtained. Note that policies regarding assessment submission, penalties and assessment feedback depend upon the individual unit of study. Details of these policies, where applicable, will be found above with other assessment details in this unit outline. All university policies can be found at http://sydney.edu.au/policy Various request forms for the Faculty of Engineering and IT can be found at http://sydney.edu.au/engineering/forms/ |
| 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.
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| Online Course Content: | Available via WebCT |
| Note on Resources: |
The on-line WebCT site provides not only copies of lecture notes, tutorials and assignments, but an interactive on-line practice tool, called SPOT, which is designed to allow students to learn and practice programming in their own time. There is also an online programming environment (access through WebCT) in which students can practice programming tasks and get instant feedback about their progress. |
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 | Lab: No lab this week |
| Lecture: Lecture 1: Matlab - Introduction to computers and programming. Getting started with Matlab (variables and data types; Matlab’s user interface; running Matlab programs to solve simple arithmetic problems). | |
| Textbook Reference - Smith: ch.1 + ch.2 | |
| Lecture: Lecture 2: Excel - Using spreadsheets: formulae, cell referencing and built-in functions | |
| Week 2 | Lecture: Lecture 1: Matlab - Arrays (creating and manipulating arrays, accessing their elements, performing mathematical and logical operations on them) |
| Lab: Weekly exercises | |
| Lecture: Lecture 2: Excel - Basic engineering modelling using spreadsheets: charts, curve fitting and What-If Scenarios | |
| Textbook Reference - Smith: ch.3, Liengme: ch. 6, 7, 9 | |
| Week 3 | Textbook Reference - Smith: ch. 4, Liengme: ch. 5, 10 |
| Lecture: Lecture 2: Excel - Logical operators and decision functions. Solving equations with Goal Seek and Solver | |
| Lecture: Lecture 1: Matlab - Execution control part 1(conditional execution: if and switch statements; loops – for and while) | |
| Lab: Weekly exercises | |
| Week 4 | Lecture: Lecture 2: Excel - Advanced modelling. Matrix calculations |
| Lab: Weekly exercises | |
| Lecture: Lecture 1: Matlab - Execution control part 2 | |
| Textbook reference - Liengme: ch. 9, 13 | |
| Week 5 | Lecture: Lecture 1: Matlab files and general input/output |
| Lab: Helpdesk sessions on Wednesday and Thursday for all students (Friday is a public holiday). | |
| Textbook Reference - Smith: ch.6 | |
| Lecture: Lecture 2: Excel input/output, integrating Excel and Matlab | |
| Week 6 | Smith: ch. 8 |
| Lecture: Lecture 2: Matlab plotting in 2D and 3D | |
| Lecture: Lecture 1: Review of Matlab and Excel concepts covered so far, in preparation for the Lab Exam. | |
| Lab: Weekly exercises | |
| Week 7 | Lecture: Lecture 2 - Functions - code reuse and the need for functions, how to create and call user-defined functions. |
| Lecture: Lecture 1: Introduction to strings in Matlab. Basic string manipulation such as slicing and concatenation. | |
| Smith: ch.5 | |
| Assessment Due: Lab Exam | |
| Week 8 | Lecture: Lecture 1: Functions - error detection and reporting, local and global variables. |
| Lab: Weekly exercises | |
| Week 9 | Lab: Weekly exercises |
| Lecture: Lecture 2: Advanced Matlab plotting - surfaces | |
| Smith: ch.7 | |
| Lecture: Lecture 1: More on Matlab functions, floating point calculations, testing and debugging your code. | |
| Week 10 | Lab: Project work |
| Lecture: Lecture 2: Advanced Matrix algebra with Matlab | |
| Smith: ch. 11 | |
| Lecture: Lecture 1: Matrix algebra with Matlab | |
| Week 11 | Lecture: Lecture 1: Introduction to solving linear equations with Matlab |
| Lecture: Lecture 2: More advanced linear equations - knowing when solutions exist. | |
| Smith: ch. 12 | |
| Lab: Weekly exercises | |
| Assessment Due: Major Project | |
| Week 12 | Lecture: Lecture 2: Polynomial interpolation, image manipulation with Matlab |
| Smith: ch. 15 | |
| Lab: Weekly exercises. | |
| Lecture: Lecture 1: Interpolation and curve fitting with Matlab | |
| Week 13 | Lecture: Lecture 2: Matlab revision and exam preparation |
| Lecture: Lecture 1: Excel revision and exam preparation | |
| Lab: Weekly exercises | |
| Exam Period | Assessment Due: Final 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:
| Attribute | Practiced | Assessed |
| Project Management and Teamwork (Level 1) | No | 0% |
| Design (Level 1) | Yes | 22.09% |
| Maths/Science Methods and Tools (Level 1) | Yes | 64.59% |
| Information Seeking (Level 1) | Yes | 0% |
| Communication (Level 1) | Yes | 5% |
| Professional Conduct (Level 1) | Yes | 8.34% |
These goals are selected from Engineering & IT Graduate Outcomes Table which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 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.
