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Unit of study_

ENGG9810: Introduction to Engineering Computing

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. Studentswill 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.

Details

Academic unit Computer Science
Unit code ENGG9810
Unit name Introduction to Engineering Computing
Session, year
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Semester 1, 2023
Attendance mode Normal day
Location Camperdown/Darlington, Sydney
Credit points 6

Enrolment rules

Prohibitions
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ENGG9801 or ENGG1801 or ENGG1810 or INFO1110 or INFO1910 or INFO1103 or INFO1903 or INFO1105 or INFO1905 or COSC1003
Prerequisites
? 
None
Corequisites
? 
None
Available to study abroad and exchange students

Yes

Teaching staff and contact details

Coordinator Xi Wu, xi.wu@sydney.edu.au
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Final Exam
Closed Book Supervised Exam
50% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Small test Lab Test 1
Online in-class assessment during tutorial time on Week 6.
10% Week 06 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO11
Small test Lab Test 2
Online in-class assessment during tutorial time on Week 12.
20% Week 12 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Small continuous assessment Revision sets
Questions to check mastery of contents.
20% Weekly Weekly based Assessment
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
hurdle task = hurdle task ?
  • Revision sets: These must be completed individually. There will be different types of questions e.g. MCQ, short responses and programming problems, that assesses your understanding of the contents covered each of every week. You will be required to complete them within the time limit. 
  • Lab Test 1: This would be an in-class assessment, taking place during tutorial time on Week 6. The lab exam will cover contents related concepts from week 1-5.
  • Lab Test 2: This would be an in-class assessment, taking place during tutorial time on Week 12. The lab exam will cover contents related concepts from week 6-11.
  • Final exam: Covers all aspects of the course. This is a closed book examination. You are not allowed to access recources etc. 

 

Detailed information for each assessment can be found on the course website: edstem.org

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

For more information see sydney.edu.au/students/guide-to-grades.

The demonstrator will provide feedback for the revision sets during the lab. It must be submitted by the due date for checking by teaching staff. 

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to the Programming Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Week 02 Storing Data and Making Decisions Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Introduction to the Programming Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5
Week 03 Repeating Actions I Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Storing Data and Making Decisions Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5
Week 04 Repeating Actions II Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Repeating Actions I Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5
Week 05 Functions I Lecture (2 hr) LO4 LO6 LO7 LO8 LO10
Repeating Actions II Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5
Week 06 Functions II Lecture (2 hr) LO4 LO6 LO7 LO8 LO10
Lab Test and Functions I Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO10
Week 07 Libraries and Modules I Lecture (2 hr) LO4 LO6 LO7 LO8 LO10 LO11
Functions II Computer laboratory (2 hr) LO4 LO6 LO7 LO8 LO10
Week 08 Libraries and Modules II Lecture (2 hr) LO4 LO6 LO7 LO8 LO10 LO11
Libraries and Modules I Computer laboratory (2 hr) LO4 LO6 LO7 LO8 LO10 LO11
Week 09 Application I Lecture (2 hr) LO1 LO2 LO3 LO5 LO6 LO9
Libraries and Modules II Computer laboratory (2 hr) LO4 LO6 LO7 LO8 LO10 LO11
Week 10 Application II Lecture (2 hr) LO1 LO2 LO3 LO5 LO6 LO9
Application I Computer laboratory (2 hr) LO1 LO2 LO3 LO5 LO6 LO9
Week 11 Case Study I Lecture (2 hr) LO1 LO2 LO3 LO8 LO9 LO11
Application II Computer laboratory (2 hr) LO1 LO2 LO3 LO5 LO6 LO9
Week 12 Case Study II Lecture (2 hr) LO1 LO2 LO3 LO4 LO6 LO10
Lab Test Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 13 Revision Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Case Study Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO6 LO8 LO9 LO10 LO11

Attendance and class requirements

Course websites:

The course website on edstem.org will contain information, including important announcements. Teaching staff will be communicating to all students and it is considered part of the course. Students are expected to regularly visit this website to know these announcements and information concerning format and schedule of assessment. The Canvas site will be used for the publishing of results. 

Attendance

Students are recommended to attend their lab class each week for feedback on assessments and learning. Students who are unable to attend a lab class will be responsible to catch up on the contents covered before the next lab class. 

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library.


Reference books:

  • Robert Sedgewick, Kevin Wayne, Robert Dondero  – Introduction to Programming in Python: An Interdisciplinary Approach. Pearson Higher Ed USA, 2015. 9780134076430
  • Pine, David J. Introduction to Python for Science and Engineering . Boca Raton, FL: CRC Press, 2019. Web.
  • Wood, M. (2015). Python and Matplotlib essentials for scientists and engineers . Morgan & Claypool Publishers.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University’s graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Develop programs to solve problems using computers.
  • LO2. Employ conventions for writing consistently readable code.
  • LO3. Compose a structured algorithmic design to solve a specified problem.
  • LO4. Apply fundamental programming principles including data types, variables and operators, flow-control: simple statements, sequences, if-then-else, loops, functions, input/output and arrays; to produce a program that solves a specified problem.
  • LO5. Compose, analyse, and trace procedural code to determine the expected output of a given program or produce a specified output.
  • LO6. Apply testing methods and assess programs through debugging with the ability to write a set of tests for a small program or function
  • LO7. Understand standard modules and packages in Python
  • LO8. Read and interpret different input formats to produce the desired outcome.
  • LO9. Apply basic numerical methods including numerical integration, curve fitting, root solving/optimisation and the least squares method
  • LO10. Write simple functions to perform computational methods including calculation of basic statistics, regression, correlation, searching, sorting on data.
  • LO11. Plot in two and three dimensions to produce an appropriate visualization of the data.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

Alignment with Competency standards

Outcomes Competency standards
LO1
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
2.3. Meaningful engagement with current technical and professional practices and issues in the designated field.
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
LO2
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
2.3. Meaningful engagement with current technical and professional practices and issues in the designated field.
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
LO3
Engineers Australia Curriculum Performance Indicators - EAPI
1. ENABLING SKILLS AND KNOWLEDGE DEVELOPMENT
2. IN-DEPTH TECHNICAL COMPETENCE
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
LO4
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
5. PRACTICAL AND ‘HANDS-ON’ EXPERIENCE
LO5
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
2.3. Meaningful engagement with current technical and professional practices and issues in the designated field.
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
5. PRACTICAL AND ‘HANDS-ON’ EXPERIENCE
LO6
Engineers Australia Curriculum Performance Indicators - EAPI
1. ENABLING SKILLS AND KNOWLEDGE DEVELOPMENT
1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice.
2. IN-DEPTH TECHNICAL COMPETENCE
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
4.2. Ability to use a systems approach to complex problems, and to design and operational performance.
LO7
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
LO8
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
LO9
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
5.1. An appreciation of the scientific method, the need for rigour and a sound theoretical basis.
5.6. Skills in the design and conduct of experiments and measurements.
Engineers Australia Curriculum Performance Indicators - EAPI
2. IN-DEPTH TECHNICAL COMPETENCE
5. PRACTICAL AND ‘HANDS-ON’ EXPERIENCE
5.6. Skills in the design and conduct of experiments and measurements.
Engineers Australia Curriculum Performance Indicators -
Competency code Taught, Practiced or Assessed Competency standard
1.1 T Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice.
1.2 T Tackling technically challenging problems from first principles.
2.1 T Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
2.2 T Application of enabling skills and knowledge to problem solution in these technical domains.
2.3 P Meaningful engagement with current technical and professional practices and issues in the designated field.
2.4 T Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity.
4.2 T Ability to use a systems approach to complex problems, and to design and operational performance.
5.1 T An appreciation of the scientific method, the need for rigour and a sound theoretical basis.
5.5 P T Skills in the development and application of mathematical, physical and conceptual models, understanding of applicability and shortcomings.
5.6 P Skills in the design and conduct of experiments and measurements.
No significant changes have been made since this unit was last offered

Every week students must:

  • Attend and take notes for the Live lecture (Mondays) or watch and take notes for the Recorded lecture 
  • Prepare for the Lab by reviewing reading, lecture and lab questions 
  • Attend and participate in weekly Lab with demonstrator (as timetabled)

IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Computer programming assignments may be checked by specialist code similarity detection software. The Faculty of Engineering currently uses the MOSS similarity detection engine (see http://theory.stanford.edu/~aiken/moss/), or the similarity report available in ED (edstem.org). These programs work in a similar way to Turnitin in that they check for similarity against a database of previously submitted assignments and code available on the internet, but they have added functionality to detect cases of similarity of holistic code structure in cases such as global search and replace of variable names, reordering of lines, changing of comment lines, and the use of white space.

All written assignments submitted in this unit of study will be submitted to the similarity detecting software program known as Turnitin. Turnitin searches for matches between text in your written assessment task and text sourced from the Internet, published works and assignments that have previously been submitted to Turnitin for analysis.

There will always be some degree of text-matching when using Turnitin. Text-matching may occur in use of direct quotations, technical terms and phrases, or the listing of bibliographic material. This does not mean you will automatically be accused of academic dishonesty or plagiarism, although Turnitin reports may be used as evidence in academic dishonesty and plagiarism decision-making processes.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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