EGD103 Computing and Data for Engineers
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | EGD103 |
|---|---|
| Antirequisite(s): | ITD104, IFB104 |
| Equivalent(s): | EGB103 |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $1,164 |
| Domestic tuition unit fee | $4,356 |
| International unit fee | $5,172 |
Unit Outline: College 1 2025, Kelvin Grove, Internal
| Unit code: | EGD103 |
|---|---|
| Credit points: | 12 |
| Equivalent: | EGB103 |
| Anti-requisite: | ITD104, IFB104 |
| Coordinator: | David Rovere | d.rovere@qut.edu.au |
Overview
Professional engineers spend much of their working lives using computing tools to support design and problem solving. In this unit, you will become proficient in designing and implementing simple algorithms to create software for solving engineering problems. As a professional engineer having computing skills are key to automating tedious tasks and creatively constructing innovative processes that go beyond off-the-shelf software solutions. With the ubiquitous nature of large data sets, whether that be about transport systems, building energy use or chemical processes, professional engineers are often required to use computing as a key tool within engineering design methods. This unit is an introductory unit providing you with foundational skills. No prior programming experience is assumed.
Learning Outcomes
On successful completion of this unit you will be able to:
- Create your own software using the programming language taught in the unit demonstrating your ability to design and implement simple algorithms.
- Manipulate engineering data flexibly and efficiently by creating your own scripts and simple programs to handle the specific tasks.
- Apply creative approaches to solve engineering problems by creating your own software.
- Ensure software is correct, clear and maintainable by applying introductory level software development principles and processes.
Content
- Python Programming
- Variables and Expressions
- Sequence, Selection and Iteration
- Data Structures
- Program Structure and Code Reuse
- Software Development and Testing Processes
- Creating Clear and Maintainable Software
- Ensuring Program Correctness
- Manipulating and Visualising Complex Engineering Data Sets
Learning Approaches
This unit takes a blended approach to learning and teaching. You will be provided with both eContent and timetabled activities. eContent will be clearly identified on your course site for you to engage with on a weekly basis before attending classes. eContent includes a combination of videos, readings, and/or exercises designed to enhance your learning experience.
During timetabled activities (for example: workshops, tutorials, practicals), the unit coordinator and/or your tutor will further explore content and you will be provided with opportunities to develop your understanding in a collaborative learning environment.
After your weekly classes, you should continue to engage with unit resources to ensure you consolidate your understanding of unit content. Teaching team members will also be available for consultations to assist you with your learning journey (further details provided on your course site).
Feedback on Learning and Assessment
During tutorials and practical classes, you will share your formative ideas around practical tasks and receive feedback from tutors. You are encouraged to view your tutorial group as a learning community and to share and discuss challenges and strategies for learning. Each assessment submission will be graded against criteria and standards which will be shared with you at the beginning of teaching period through Assessment Task Descriptions and Marking Rubrics. Marked assessment will include feedback from markers against the criteria.
Assessment
Overview
Assessment in this unit aims is to build understanding and skills in programming, while illustrating the vast practical value of programming in all engineering fields. To emphasise the practical value for engineers, this unit will address authentic problems related to multiple fields of engineering. Emphasis will be given to increasing productivity by flexibly and efficiently manipulating data but will expand to show how creating algorithmic solutions can lead to creative and innovative approaches to engineering problems.
No prior programming experience is assumed. Basic programming skills will be developed progressively throughout the teaching period starting with very simple well defined exercises, reinforced through repetition until designing simple algorithms via sequence, selection and repetition becomes second nature. Problems will become progressively more complex and open ended, requiring you to make more decisions for yourself.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Programming exercises
This assessment piece will consist of engineering problems that can be solved with foundational programming practices. The exercises are split into two parts. Part A is due early in the semester to provide formative feedback on introductory programming concepts prior to Census date. Part B is due mid-semester and has a large emphasis on control flow and data structures. Test cases are provided in both parts to provide you with immediate learning feedback.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Data manipulation and integration
This assignment will require you to process multiple real-world data sets to gain insights about an engineering system. You will be required to import, inspect, combine and clean data prior to analysis. You will then summarise information within the data using aggregation and visualisation techniques. You will also design and implement your own algorithms to creatively solve a problem using the data.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Final exam
The final examination will assess your knowledge and understanding of the concepts addressed throughout the semester. You will be expected to answer conceptual questions about computing and data for engineers. You will also be expected to write code to solve small programming and data processing tasks.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There is no single textbook recommended for purchase for this unit. The unit includes a structured introduction to Python and there is a wide range of supporting resources available online for Python programming and data science. Online resources are an essential part of modern computing and many will be introduced as they are needed during the teaching period.
Risk Assessment Statement
There are no unusual health or safety risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.EN02 Diploma in Engineering
- Manage projects to solve complex engineering problems, using appropriate information, engineering methods, and technologies.
Relates to: ULO2, ULO3, ULO4, Data manipulation and integration, Final exam - Demonstrate foundational knowledge and skills of physical, mathematical, statistical, computer, and information sciences that are fundamental to professional engineering practice.
Relates to: ULO1, Programming exercises, Data manipulation and integration, Final exam
Unit Outline: College 2 2025, Kelvin Grove, Internal
| Unit code: | EGD103 |
|---|---|
| Credit points: | 12 |
| Equivalent: | EGB103 |
| Anti-requisite: | ITD104, IFB104 |
Overview
Professional engineers spend much of their working lives using computing tools to support design and problem solving. In this unit, you will become proficient in designing and implementing simple algorithms to create software for solving engineering problems. As a professional engineer having computing skills are key to automating tedious tasks and creatively constructing innovative processes that go beyond off-the-shelf software solutions. With the ubiquitous nature of large data sets, whether that be about transport systems, building energy use or chemical processes, professional engineers are often required to use computing as a key tool within engineering design methods. This unit is an introductory unit providing you with foundational skills. No prior programming experience is assumed.
Learning Outcomes
On successful completion of this unit you will be able to:
- Create your own software using the programming language taught in the unit demonstrating your ability to design and implement simple algorithms.
- Manipulate engineering data flexibly and efficiently by creating your own scripts and simple programs to handle the specific tasks.
- Apply creative approaches to solve engineering problems by creating your own software.
- Ensure software is correct, clear and maintainable by applying introductory level software development principles and processes.
Content
- Python Programming
- Variables and Expressions
- Sequence, Selection and Iteration
- Data Structures
- Program Structure and Code Reuse
- Software Development and Testing Processes
- Creating Clear and Maintainable Software
- Ensuring Program Correctness
- Manipulating and Visualising Complex Engineering Data Sets
Learning Approaches
This unit takes a blended approach to learning and teaching. You will be provided with both eContent and timetabled activities. eContent will be clearly identified on your course site for you to engage with on a weekly basis before attending classes. eContent includes a combination of videos, readings, and/or exercises designed to enhance your learning experience.
During timetabled activities (for example: workshops, tutorials, practicals), the unit coordinator and/or your tutor will further explore content and you will be provided with opportunities to develop your understanding in a collaborative learning environment.
After your weekly classes, you should continue to engage with unit resources to ensure you consolidate your understanding of unit content. Teaching team members will also be available for consultations to assist you with your learning journey (further details provided on your course site).
Feedback on Learning and Assessment
During tutorials and practical classes, you will share your formative ideas around practical tasks and receive feedback from tutors. You are encouraged to view your tutorial group as a learning community and to share and discuss challenges and strategies for learning. Each assessment submission will be graded against criteria and standards which will be shared with you at the beginning of teaching period through Assessment Task Descriptions and Marking Rubrics. Marked assessment will include feedback from markers against the criteria.
Assessment
Overview
Assessment in this unit aims is to build understanding and skills in programming, while illustrating the vast practical value of programming in all engineering fields. To emphasise the practical value for engineers, this unit will address authentic problems related to multiple fields of engineering. Emphasis will be given to increasing productivity by flexibly and efficiently manipulating data but will expand to show how creating algorithmic solutions can lead to creative and innovative approaches to engineering problems.
No prior programming experience is assumed. Basic programming skills will be developed progressively throughout the teaching period starting with very simple well defined exercises, reinforced through repetition until designing simple algorithms via sequence, selection and repetition becomes second nature. Problems will become progressively more complex and open ended, requiring you to make more decisions for yourself.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Programming exercises
This assessment piece will consist of engineering problems that can be solved with foundational programming practices. The exercises are split into two parts. Part A is due early in the semester to provide formative feedback on introductory programming concepts prior to Census date. Part B is due mid-semester and has a large emphasis on control flow and data structures. Test cases are provided in both parts to provide you with immediate learning feedback.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Data manipulation and integration
This assignment will require you to process multiple real-world data sets to gain insights about an engineering system. You will be required to import, inspect, combine and clean data prior to analysis. You will then summarise information within the data using aggregation and visualisation techniques. You will also design and implement your own algorithms to creatively solve a problem using the data.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Final exam
The final examination will assess your knowledge and understanding of the concepts addressed throughout the semester. You will be expected to answer conceptual questions about computing and data for engineers. You will also be expected to write code to solve small programming and data processing tasks.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There is no single textbook recommended for purchase for this unit. The unit includes a structured introduction to Python and there is a wide range of supporting resources available online for Python programming and data science. Online resources are an essential part of modern computing and many will be introduced as they are needed during the teaching period.
Risk Assessment Statement
There are no unusual health or safety risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.EN02 Diploma in Engineering
- Manage projects to solve complex engineering problems, using appropriate information, engineering methods, and technologies.
Relates to: ULO2, ULO3, ULO4, Data manipulation and integration, Final exam - Demonstrate foundational knowledge and skills of physical, mathematical, statistical, computer, and information sciences that are fundamental to professional engineering practice.
Relates to: ULO1, Programming exercises, Data manipulation and integration, Final exam
Unit Outline: College Summer 2025, Kelvin Grove, Internal
| Unit code: | EGD103 |
|---|---|
| Credit points: | 12 |
| Equivalent: | EGB103 |
| Anti-requisite: | ITD104, IFB104 |
Overview
Professional engineers spend much of their working lives using computing tools to support design and problem solving. In this unit, you will become proficient in designing and implementing simple algorithms to create software for solving engineering problems. As a professional engineer having computing skills are key to automating tedious tasks and creatively constructing innovative processes that go beyond off-the-shelf software solutions. With the ubiquitous nature of large data sets, whether that be about transport systems, building energy use or chemical processes, professional engineers are often required to use computing as a key tool within engineering design methods. This unit is an introductory unit providing you with foundational skills. No prior programming experience is assumed.
Learning Outcomes
On successful completion of this unit you will be able to:
- Create your own software using the programming language taught in the unit demonstrating your ability to design and implement simple algorithms.
- Manipulate engineering data flexibly and efficiently by creating your own scripts and simple programs to handle the specific tasks.
- Apply creative approaches to solve engineering problems by creating your own software.
- Ensure software is correct, clear and maintainable by applying introductory level software development principles and processes.
Content
- Python Programming
- Variables and Expressions
- Sequence, Selection and Iteration
- Data Structures
- Program Structure and Code Reuse
- Software Development and Testing Processes
- Creating Clear and Maintainable Software
- Ensuring Program Correctness
- Manipulating and Visualising Complex Engineering Data Sets
Learning Approaches
This unit takes a blended approach to learning and teaching. You will be provided with both eContent and timetabled activities. eContent will be clearly identified on your course site for you to engage with on a weekly basis before attending classes. eContent includes a combination of videos, readings, and/or exercises designed to enhance your learning experience.
During timetabled activities (for example: workshops, tutorials, practicals), the unit coordinator and/or your tutor will further explore content and you will be provided with opportunities to develop your understanding in a collaborative learning environment.
After your weekly classes, you should continue to engage with unit resources to ensure you consolidate your understanding of unit content. Teaching team members will also be available for consultations to assist you with your learning journey (further details provided on your course site).
Feedback on Learning and Assessment
During tutorials and practical classes, you will share your formative ideas around practical tasks and receive feedback from tutors. You are encouraged to view your tutorial group as a learning community and to share and discuss challenges and strategies for learning. Each assessment submission will be graded against criteria and standards which will be shared with you at the beginning of teaching period through Assessment Task Descriptions and Marking Rubrics. Marked assessment will include feedback from markers against the criteria.
Assessment
Overview
Assessment in this unit aims is to build understanding and skills in programming, while illustrating the vast practical value of programming in all engineering fields. To emphasise the practical value for engineers, this unit will address authentic problems related to multiple fields of engineering. Emphasis will be given to increasing productivity by flexibly and efficiently manipulating data but will expand to show how creating algorithmic solutions can lead to creative and innovative approaches to engineering problems.
No prior programming experience is assumed. Basic programming skills will be developed progressively throughout the teaching period starting with very simple well defined exercises, reinforced through repetition until designing simple algorithms via sequence, selection and repetition becomes second nature. Problems will become progressively more complex and open ended, requiring you to make more decisions for yourself.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Programming exercises
This assessment piece will consist of engineering problems that can be solved with foundational programming practices. The exercises are split into two parts. Part A is due early in the semester to provide formative feedback on introductory programming concepts prior to Census date. Part B is due mid-semester and has a large emphasis on control flow and data structures. Test cases are provided in both parts to provide you with immediate learning feedback.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Data manipulation and integration
This assignment will require you to process multiple real-world data sets to gain insights about an engineering system. You will be required to import, inspect, combine and clean data prior to analysis. You will then summarise information within the data using aggregation and visualisation techniques. You will also design and implement your own algorithms to creatively solve a problem using the data.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Final exam
The final examination will assess your knowledge and understanding of the concepts addressed throughout the semester. You will be expected to answer conceptual questions about computing and data for engineers. You will also be expected to write code to solve small programming and data processing tasks.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There is no single text book recommended for purchase for this unit. The unit includes a structured introduction to Python and there is a wide range of supporting resources available online for Python programming and data science. Online resources are an essential part of modern computing and many will be introduced as they are needed during the teaching period.
Risk Assessment Statement
There are no unusual health or safety risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.EN02 Diploma in Engineering
- Manage projects to solve complex engineering problems, using appropriate information, engineering methods, and technologies.
Relates to: ULO2, ULO3, ULO4, Data manipulation and integration, Final exam - Demonstrate foundational knowledge and skills of physical, mathematical, statistical, computer, and information sciences that are fundamental to professional engineering practice.
Relates to: ULO1, Programming exercises, Data manipulation and integration, Final exam